Welcome to EMI/EMC in Power Electronics (2025)
Description: With a rapid advancement of power switching devices and digital signal processing units, power electronics technology has found its way into many applications of renewable energy generation, transmission, and consumption. Although power electronics systems are a key enabler as a cross-functional technology in the energy conversion process, their pulse energy conversion with inherent switching behavior exhibits disturbing harmonic emissions and electromagnetic noises.
Recently, with the high penetration of power electronic systems and advent of new power semiconductor devices known as wide-band gap (WBG) the importance of understanding and preventing power converter switching disturbances has significantly elevated. The generated harmonic and noise disturbances can result in electromagnetic interference (EMI) and should be controlled within specific limits by applying proper filtering, topology, and control schemes. Thereby, to prevent the power converters from disturbing their own operation and other nearby electronic devices they should be designed for electromagnetic compatibility (EMC).
The emphasis of this course is to give a complete and clear picture of EMI issues and mitigation methodologies. Systematic designing of passive EMI filters for differential mode (DM) and common mode (CM) noises in single-phase and three-phase systems will be provided. Printed circuit board (PCB) design criteria, passive and active components parasitic and shielding approaches in reducing near-field couplings will be covered as well. Furthermore, time and frequency domain modeling of conducted low and high frequency emission noises through developing equivalent circuit models of power electronics converters to reduce the analysis complexity and prevent from conventional trial and error design approach will be addressed. This course will also focus on new challenges within the new frequency band of 2-150 kHz in power electronic based power systems. The course content is combined with real-world application examples and demonstrations.
In the first day, the course will focus on the basics of harmonics generated by switching, EMI issues in PWM converters, components parasitic, measurement requirements, interference mechanisms, filtering components and strategies. In the second day, there will be more focus on advanced topics such as magnetic coupling, EMI prediction, Shielding and new standard requirements. The second day will be supported with industrial examples and real-world design experience regarding different aspects of EMI/EMC in power electronics. In the third day, the course will dig into the details of parasitic capacitances in magnetic components, practically showing the measurement methods of using an impedance analyzer. The recent research on numerical and analytical EMI/modelling and supraharmonics will also be introduced in the third day.
Key words: Electromagnetic Interference, Electromagnetic Compatibility, Power Electronics, Supraharmonics, EMI Prediction, EMI filter design
Prerequisites: This course is intended for intermediate and advanced researchers and engineers in the field of power electronics and its applications, for EMC specialists and advanced university students exploring new harmonics and EMI challenges in power electronics-based power systems and WBG-based power electronic systems. General knowledge in power electronics converter operation modes, passive components and basic control theory are preferred. Course exercises and mini projects will be performed on MATLAB/LTSPICE software platform.
Learning objectives:
1- EMI Prediction and Filtering in Power Electronics
2- Understanding EMI mechanisms and EMC Design Strategy in Power Electronics
3- Analytical Modeling and Parasitic Measurement
Teaching methods: Lectures, Group work, Presentations, Excercise, Demonstration
Form of evaluation: The participants will work on the design for EMC exercises from the final 1st day of lecture. Two to three design exercises will be provided. The exercises are defined based on a real application design and one exercise will be assigned to a group of four people. The participants are required to study the exercises prior to the lecture. In the 2nd day of lecture, the groups will start to work on their mini projects, with necessary support and Q&A by the lecturers. Groups will continue to compare and deeply discuss their design method and choices on the 3rd day and present their results and solutions in a presentation form to the class during the 3rd day to get feedback from the lecturers to better work out their solutions. Later each group will have one week after the lecture to submit their solutions to the course coordinator in a pdf format for final evaluation.
Criteria for assessment:
1 - Written report with solutions on the power electronics EMI/EMC design exercise
2- Powerpoint presentation
Remarks: In total 56 hours [20 hours for Preparations, 22 hours for Teaching, 8 hours for Practicing and Assignment, and 6 hours for finalizing report.]
Key literature: TBA
Organizer: Associate Professor Pooya Davari, pda@energy.aau.dk
Lecturers:
Professor Eckart Hoene - Aalborg University and Fraunhofer IZM,
Dr. Christian Wolf, Lead Specialist, EMC & Power Electronics - Grundfos Holding A/S,
Associate Professor Pooya Davari - Aalborg University
Assistant Professor Hongbo Zhao – Aalborg University
External lecturers: Professor Eckart Hoene - Aalborg University and Fraunhofer IZM, Dr. Christian Wolf, Lead Specialist, EMC & Power Electronics - Grundfos Holding A/S
ECTS: 2.0
Time: 11, 12, 13 November 2025
Place: Aalborg University (AAU Energy - Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 21 October 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: With a rapid advancement of power switching devices and digital signal processing units, power electronics technology has found its way into many applications of renewable energy generation, transmission, and consumption. Although power electronics systems are a key enabler as a cross-functional technology in the energy conversion process, their pulse energy conversion with inherent switching behavior exhibits disturbing harmonic emissions and electromagnetic noises.
Recently, with the high penetration of power electronic systems and advent of new power semiconductor devices known as wide-band gap (WBG) the importance of understanding and preventing power converter switching disturbances has significantly elevated. The generated harmonic and noise disturbances can result in electromagnetic interference (EMI) and should be controlled within specific limits by applying proper filtering, topology, and control schemes. Thereby, to prevent the power converters from disturbing their own operation and other nearby electronic devices they should be designed for electromagnetic compatibility (EMC).
The emphasis of this course is to give a complete and clear picture of EMI issues and mitigation methodologies. Systematic designing of passive EMI filters for differential mode (DM) and common mode (CM) noises in single-phase and three-phase systems will be provided. Printed circuit board (PCB) design criteria, passive and active components parasitic and shielding approaches in reducing near-field couplings will be covered as well. Furthermore, time and frequency domain modeling of conducted low and high frequency emission noises through developing equivalent circuit models of power electronics converters to reduce the analysis complexity and prevent from conventional trial and error design approach will be addressed. This course will also focus on new challenges within the new frequency band of 2-150 kHz in power electronic based power systems. The course content is combined with real-world application examples and demonstrations.
In the first day, the course will focus on the basics of harmonics generated by switching, EMI issues in PWM converters, components parasitic, measurement requirements, interference mechanisms, filtering components and strategies. In the second day, there will be more focus on advanced topics such as magnetic coupling, EMI prediction, Shielding and new standard requirements. The second day will be supported with industrial examples and real-world design experience regarding different aspects of EMI/EMC in power electronics. In the third day, the course will dig into the details of parasitic capacitances in magnetic components, practically showing the measurement methods of using an impedance analyzer. The recent research on numerical and analytical EMI/modelling and supraharmonics will also be introduced in the third day.
Key words: Electromagnetic Interference, Electromagnetic Compatibility, Power Electronics, Supraharmonics, EMI Prediction, EMI filter design
Prerequisites: This course is intended for intermediate and advanced researchers and engineers in the field of power electronics and its applications, for EMC specialists and advanced university students exploring new harmonics and EMI challenges in power electronics-based power systems and WBG-based power electronic systems. General knowledge in power electronics converter operation modes, passive components and basic control theory are preferred. Course exercises and mini projects will be performed on MATLAB/LTSPICE software platform.
Learning objectives:
1- EMI Prediction and Filtering in Power Electronics
2- Understanding EMI mechanisms and EMC Design Strategy in Power Electronics
3- Analytical Modeling and Parasitic Measurement
Teaching methods: Lectures, Group work, Presentations, Excercise, Demonstration
Form of evaluation: The participants will work on the design for EMC exercises from the final 1st day of lecture. Two to three design exercises will be provided. The exercises are defined based on a real application design and one exercise will be assigned to a group of four people. The participants are required to study the exercises prior to the lecture. In the 2nd day of lecture, the groups will start to work on their mini projects, with necessary support and Q&A by the lecturers. Groups will continue to compare and deeply discuss their design method and choices on the 3rd day and present their results and solutions in a presentation form to the class during the 3rd day to get feedback from the lecturers to better work out their solutions. Later each group will have one week after the lecture to submit their solutions to the course coordinator in a pdf format for final evaluation.
Criteria for assessment:
1 - Written report with solutions on the power electronics EMI/EMC design exercise
2- Powerpoint presentation
Remarks: In total 56 hours [20 hours for Preparations, 22 hours for Teaching, 8 hours for Practicing and Assignment, and 6 hours for finalizing report.]
Key literature: TBA
Organizer: Associate Professor Pooya Davari, pda@energy.aau.dk
Lecturers:
Professor Eckart Hoene - Aalborg University and Fraunhofer IZM,
Dr. Christian Wolf, Lead Specialist, EMC & Power Electronics - Grundfos Holding A/S,
Associate Professor Pooya Davari - Aalborg University
Assistant Professor Hongbo Zhao – Aalborg University
External lecturers: Professor Eckart Hoene - Aalborg University and Fraunhofer IZM, Dr. Christian Wolf, Lead Specialist, EMC & Power Electronics - Grundfos Holding A/S
ECTS: 2.0
Time: 11, 12, 13 November 2025
Place: Aalborg University (AAU Energy - Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 21 October 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Pooya Davari
- Teacher: Eckart Hoene
- Teacher: Christian Wolf
- Teacher: Hongbo Zhao
Welcome to Batteries: from fundamentals to applications (2025)
Description: Batteries play an undeniable role in the green transition, enabling the shift to renewable energy by storing and distributing power from intermittent sources like solar and wind. As demand for cleaner energy grows, trends point towards advancements in battery efficiency, energy density, and sustainability, driving widespread adoption of electric vehicles and stationary battery storage. While pivotal in modern technology, batteries present several significant challenges. One major issue is performance variability, which can be influenced by factors like temperature, usage patterns, and charging rates. Over time, all batteries degrade, losing capacity and efficiency due to electrochemical reactions within the cells. Accurately estimating the state of charge (SOC) is complex, often requiring sophisticated algorithms to provide reliable data, as simple voltage measurements can be misleading. Similarly, assessing the state of health (SOH) is crucial yet challenging; it involves tracking the battery’s aging process and predicting remaining useful life, which is influenced by various environmental and operational conditions. Lifetime prediction is another critical aspect, necessitating comprehensive models that account for all possible degradation mechanisms to ensure reliability and safety. Moreover, the degradation process can lead to issues such as reduced energy density, increased internal resistance, and potential safety hazards like thermal runaway. Balancing these factors while striving for longer-lasting, higher-performing batteries is an ongoing struggle for both researchers, manufacturers, and end-users.
All these aspects will be thoroughly covered in this comprehensive 5-day PhD course designed for beginner and intermediate learners in the field. The course will delve into the complexities of battery performance, degradation mechanisms, SOC and SOH estimation techniques, lifetime prediction models and battery operation in real-life applications. This intensive program aims to provide participants with the knowledge and skills necessary to tackle current challenges and drive future innovations in battery technology.
Key words: Batteries, Performance and Degradation, Electrochemistry, State Estimation, Electro-Thermal Modeling, Stationary Applications
Prerequisites: The participants should have knowledge and competencies comparable to those of an engineer with an MSc in electrical engineering. Furthermore, they should be familiar with MATLAB/Simulink or any other programming software (e.g., Python, C++, etc.) to complete the assignments. It is up to the course participants to decide which software they would like to use to complete the assignments.
Learning objectives: After successfully completing this PhD course, the participants will be able to:
- Identify the most suitable battery chemistry for specific applications, with respect to performance characteristics and lifetime expectations.
- Develop and parametrize battery performance (electrical and thermal) models utilizing battery data sheets and laboratory characterization tests.
- Select the appropriate SOC/SOH estimation algorithm based on the application-specific requirements (e.g., accuracy, computation complexity, etc.).
- Parametrize SOC and SOH algorithms using data obtained from laboratory performance characterization and lifetime testing.
- Understand the relationship between macro-scale battery degradation (e.g., capacity fade, resistance increase etc.) and micro-scale phenomena (e.g., lithium plating, mechanical cracking, SEI layer formation etc.) to inform battery lifetime estimation models.
- Utilize the battery models and state estimation algorithms in real-life battery operation scenarios.
- Teaching methods: Lectures with active participation of the participants
Form of evaluation: Each participant should submit an individual report detailing the solution of all the assignments. The assignments are introduced during specific lectures and are to be solved by the course participants after the course. The report should be submitted no later than one month after the course is finished.
Criteria for assessment: To graduate the course, the participants should complete correctly at least 50% of each assignment.
Remarks: 84 hours (preparation based on the provided literature: 10 hours; lectures: 32 hours; solving of assignments: 26 hours; report writing: 16 hours)
Key literature: TBA
Organizer: Associate Professor Daniel-Ioan Stroe, dis@energy.aau.dk
Lecturers:
Assoc. Prof. Daniel-Ioan Stroe (Section B)
Assoc. Prof. Erik Schaltz (Section D)
Assoc. Prof. Florin Iov (Section B)
Assoc. Prof. Tamas Kerekes (Section B)
Postdoc Yaqi Li (Section E)
Assist. Prof. Søren B. Vilsen (Department of Mathematics)
ECTS: 3.0
Time: 3, 4, 5, 6, 7 November 2025
Place: Aalborg University (Hybrid (AAU Energy in Aalborg & online by Teams))
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 13 October 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: Batteries play an undeniable role in the green transition, enabling the shift to renewable energy by storing and distributing power from intermittent sources like solar and wind. As demand for cleaner energy grows, trends point towards advancements in battery efficiency, energy density, and sustainability, driving widespread adoption of electric vehicles and stationary battery storage. While pivotal in modern technology, batteries present several significant challenges. One major issue is performance variability, which can be influenced by factors like temperature, usage patterns, and charging rates. Over time, all batteries degrade, losing capacity and efficiency due to electrochemical reactions within the cells. Accurately estimating the state of charge (SOC) is complex, often requiring sophisticated algorithms to provide reliable data, as simple voltage measurements can be misleading. Similarly, assessing the state of health (SOH) is crucial yet challenging; it involves tracking the battery’s aging process and predicting remaining useful life, which is influenced by various environmental and operational conditions. Lifetime prediction is another critical aspect, necessitating comprehensive models that account for all possible degradation mechanisms to ensure reliability and safety. Moreover, the degradation process can lead to issues such as reduced energy density, increased internal resistance, and potential safety hazards like thermal runaway. Balancing these factors while striving for longer-lasting, higher-performing batteries is an ongoing struggle for both researchers, manufacturers, and end-users.
All these aspects will be thoroughly covered in this comprehensive 5-day PhD course designed for beginner and intermediate learners in the field. The course will delve into the complexities of battery performance, degradation mechanisms, SOC and SOH estimation techniques, lifetime prediction models and battery operation in real-life applications. This intensive program aims to provide participants with the knowledge and skills necessary to tackle current challenges and drive future innovations in battery technology.
Key words: Batteries, Performance and Degradation, Electrochemistry, State Estimation, Electro-Thermal Modeling, Stationary Applications
Prerequisites: The participants should have knowledge and competencies comparable to those of an engineer with an MSc in electrical engineering. Furthermore, they should be familiar with MATLAB/Simulink or any other programming software (e.g., Python, C++, etc.) to complete the assignments. It is up to the course participants to decide which software they would like to use to complete the assignments.
Learning objectives: After successfully completing this PhD course, the participants will be able to:
- Identify the most suitable battery chemistry for specific applications, with respect to performance characteristics and lifetime expectations.
- Develop and parametrize battery performance (electrical and thermal) models utilizing battery data sheets and laboratory characterization tests.
- Select the appropriate SOC/SOH estimation algorithm based on the application-specific requirements (e.g., accuracy, computation complexity, etc.).
- Parametrize SOC and SOH algorithms using data obtained from laboratory performance characterization and lifetime testing.
- Understand the relationship between macro-scale battery degradation (e.g., capacity fade, resistance increase etc.) and micro-scale phenomena (e.g., lithium plating, mechanical cracking, SEI layer formation etc.) to inform battery lifetime estimation models.
- Utilize the battery models and state estimation algorithms in real-life battery operation scenarios.
- Teaching methods: Lectures with active participation of the participants
Form of evaluation: Each participant should submit an individual report detailing the solution of all the assignments. The assignments are introduced during specific lectures and are to be solved by the course participants after the course. The report should be submitted no later than one month after the course is finished.
Criteria for assessment: To graduate the course, the participants should complete correctly at least 50% of each assignment.
Remarks: 84 hours (preparation based on the provided literature: 10 hours; lectures: 32 hours; solving of assignments: 26 hours; report writing: 16 hours)
Key literature: TBA
Organizer: Associate Professor Daniel-Ioan Stroe, dis@energy.aau.dk
Lecturers:
Assoc. Prof. Daniel-Ioan Stroe (Section B)
Assoc. Prof. Erik Schaltz (Section D)
Assoc. Prof. Florin Iov (Section B)
Assoc. Prof. Tamas Kerekes (Section B)
Postdoc Yaqi Li (Section E)
Assist. Prof. Søren B. Vilsen (Department of Mathematics)
ECTS: 3.0
Time: 3, 4, 5, 6, 7 November 2025
Place: Aalborg University (Hybrid (AAU Energy in Aalborg & online by Teams))
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 13 October 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Florin Iov
- Teacher: Tamas Kerekes
- Teacher: Yaqi Li
- Teacher: Erik Schaltz
- Teacher: Daniel-Ioan Stroe
- Teacher: Søren Byg Vilsen
Welcome to Introduction to Model Predictive Control for Power Electronics Converters (2025)
Description: After the introduction of fast-processing digital signal processors Model Predictive Control (MPC) has emerged as one of the most promising control alternatives for power electronics converter control. The advantages of MPC algorithms over traditional cascade control structures lie in fast transient response and the simple inclusion of multiple control objectives in a single control loop. However, there also remain challenges in the implementation of MPC algorithms in power electronics converter applications. Although some variants of the MPC algorithm have found application in industrial products, further research is required to achieve a much wider application.
In this course basic principles of MPC will be explained, thus the course is suitable for participants without prior knowledge about MPC applications. The focus will be on the two most popular MPC algorithms in power electronics applications: finite control set (FS-MPC) and continuous control set (CS-MPC). Afterwards, the emphasis will be put on specific challenges in algorithm implementation e.g. weighting factor tunning, computational burden, fixing the switching frequency, and performance verification using statistical model checking. Several applications of MPC algorithm applications will be analyzed e.g. grid-connected converters, multilevel converters, motor drives, UPS converters. The course will be accompanied by hands-on Simulation exercises where the participants can apply the learned methods and understand the principles of algorithm implementation.
Key words: finite-set control, model predictive control, model checking, motor drives control, power electronics converters
Prerequisites:
- Fundamentals of power electronics
- Experience with MATLAB/Simulink is recommended for the exercises
Learning objectives:
- Understand fundamentals of model predictive control in power electronics applications
- How to implement the basic model predictive current control for VSC converters
- How to implement the basic model predictive control for motor drives
- Understand the challenges of MPC implementation and how to address them
- Model a power electronics converter system using timed automata and apply statistical model checking to validate its performance
- Teaching methods: Lectures, Presentations, Excercise
Form of evaluation: Students are required to solve exercises using the knowledge acquired in the course and submit a short project report with solutions within three weeks after the course, which will be assessed by the lecturers.
Criteria for assessment: Completed exercise and submitted mini report.
Remarks: In total 46 hours (Preparation: 12 hours, Lecture: 16 hours, Exercise and final report: 18 hours)
Key literature: TBA
Organizer: Professor Frede Blaabjerg, fbl@energy.aau.dk
Lecturers:
Assistant Professor Mateja Novak, Aalborg University, (AAU Energy)
Associate Professor Ulrik Nyman, Aalborg University (Computer Science Department)
ECTS: 2.0
Time: 2 and 3 October 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 11 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: After the introduction of fast-processing digital signal processors Model Predictive Control (MPC) has emerged as one of the most promising control alternatives for power electronics converter control. The advantages of MPC algorithms over traditional cascade control structures lie in fast transient response and the simple inclusion of multiple control objectives in a single control loop. However, there also remain challenges in the implementation of MPC algorithms in power electronics converter applications. Although some variants of the MPC algorithm have found application in industrial products, further research is required to achieve a much wider application.
In this course basic principles of MPC will be explained, thus the course is suitable for participants without prior knowledge about MPC applications. The focus will be on the two most popular MPC algorithms in power electronics applications: finite control set (FS-MPC) and continuous control set (CS-MPC). Afterwards, the emphasis will be put on specific challenges in algorithm implementation e.g. weighting factor tunning, computational burden, fixing the switching frequency, and performance verification using statistical model checking. Several applications of MPC algorithm applications will be analyzed e.g. grid-connected converters, multilevel converters, motor drives, UPS converters. The course will be accompanied by hands-on Simulation exercises where the participants can apply the learned methods and understand the principles of algorithm implementation.
Key words: finite-set control, model predictive control, model checking, motor drives control, power electronics converters
Prerequisites:
- Fundamentals of power electronics
- Experience with MATLAB/Simulink is recommended for the exercises
Learning objectives:
- Understand fundamentals of model predictive control in power electronics applications
- How to implement the basic model predictive current control for VSC converters
- How to implement the basic model predictive control for motor drives
- Understand the challenges of MPC implementation and how to address them
- Model a power electronics converter system using timed automata and apply statistical model checking to validate its performance
- Teaching methods: Lectures, Presentations, Excercise
Form of evaluation: Students are required to solve exercises using the knowledge acquired in the course and submit a short project report with solutions within three weeks after the course, which will be assessed by the lecturers.
Criteria for assessment: Completed exercise and submitted mini report.
Remarks: In total 46 hours (Preparation: 12 hours, Lecture: 16 hours, Exercise and final report: 18 hours)
Key literature: TBA
Organizer: Professor Frede Blaabjerg, fbl@energy.aau.dk
Lecturers:
Assistant Professor Mateja Novak, Aalborg University, (AAU Energy)
Associate Professor Ulrik Nyman, Aalborg University (Computer Science Department)
ECTS: 2.0
Time: 2 and 3 October 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 11 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Frede Blaabjerg
- Teacher: Mateja Novak
- Teacher: Ulrik Nyman
Welcome to Three-Level Neutral-Point-Clamped Converters: State-of-the-art and Recent Advances in Control Solutions and Reliability (2025)
Description: The three-level neutral-point-clamped (3L-NPC) converters have been widely applied in several applications including motor drives and grid integration such as wind and solar energy systems. Key performance metrics of the 3L-NPC converters like power quality, efficiency, power density and reliability are strongly affected by the used control methods. Therefore, different control methods have been proposed for the 3L-NPC topology to address certain aspects.
This course aims to address basic concepts and control design challenges of NPC converter applications. It will start with basic operating principles of the topology and their control challenges such as neutral point voltage balancing and thermal stress distribution. Then, two different control approaches will be presented: 1) carrier-based PWM techniques and 2) model predictive control techniques. For each control technique, basic concept and step-by-step implementation guideline will be provided, followed by more application-oriented examples and implementation challenges.
An approach to analyze the reliability of power electronics converters will also be introduced, which includes thermal stress modeling, lifetime prediction, and reliability evaluation (Monte Carlo simulation). It will be demonstrated that control algorithm selection has a major impact on the reliability of semiconductor devices and DC-link capacitors in NPC converters. In the last part of the course the focus will be set on practical application cases of NPC converters in the industry.
The course is intended both for academia researchers and industry, who do not have previous knowledge about the NPC topology (basic operating principles will be explained), and for those who are familiar with the topology and would like to learn more about ongoing research directions and novel control solutions.
Key words: Control algorithm, lifetime, multilevel converters, neutral point clamped, modulation, model predictive control, reliability
Prerequisites:
- Fundamentals of power electronics
- Experience with MATLAB/Simulink is recommended for the exercises
Learning objectives:
- Understand fundamentals of 3L-NPC and required control objectives (neutral point voltage balance, thermal stress distribution)
- Implement the basic carrier-based control methods for 3L-NPC
- Implement the model predictive control methods for 3L-NPC
- Understand how control selection affects the reliability of components in the 3L-NPC
- Practical design considerations for NPC converters
Teaching methods: Lectures, Excercise, Presentations
Form of evaluation: Students are required to solve exercises using the knowledge acquired in the course and submit a short project report with solutions within three weeks after the course, which will be assessed by the lecturers.
Criteria for assessment: Completed exercises (2) submitted as a short report
Remarks: In total about 46 hours (Preparation: 12 hours, Lecture: 16 hours, Exercise and final report: 18 hours)
Key literature: TBA
Organizer: Frede Blaabjerg, fbl@energy.aau.dk
Lecturers:
Assistant Prof. Ariya Sangwongwanich
Assistant Prof. Mateja Novak
External lecturers: Radu Dan Lazar, Reserach Engineer, Danfoss Drives
ECTS: 2.0
Time: 25 and 26 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 4 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: The three-level neutral-point-clamped (3L-NPC) converters have been widely applied in several applications including motor drives and grid integration such as wind and solar energy systems. Key performance metrics of the 3L-NPC converters like power quality, efficiency, power density and reliability are strongly affected by the used control methods. Therefore, different control methods have been proposed for the 3L-NPC topology to address certain aspects.
This course aims to address basic concepts and control design challenges of NPC converter applications. It will start with basic operating principles of the topology and their control challenges such as neutral point voltage balancing and thermal stress distribution. Then, two different control approaches will be presented: 1) carrier-based PWM techniques and 2) model predictive control techniques. For each control technique, basic concept and step-by-step implementation guideline will be provided, followed by more application-oriented examples and implementation challenges.
An approach to analyze the reliability of power electronics converters will also be introduced, which includes thermal stress modeling, lifetime prediction, and reliability evaluation (Monte Carlo simulation). It will be demonstrated that control algorithm selection has a major impact on the reliability of semiconductor devices and DC-link capacitors in NPC converters. In the last part of the course the focus will be set on practical application cases of NPC converters in the industry.
The course is intended both for academia researchers and industry, who do not have previous knowledge about the NPC topology (basic operating principles will be explained), and for those who are familiar with the topology and would like to learn more about ongoing research directions and novel control solutions.
Key words: Control algorithm, lifetime, multilevel converters, neutral point clamped, modulation, model predictive control, reliability
Prerequisites:
- Fundamentals of power electronics
- Experience with MATLAB/Simulink is recommended for the exercises
Learning objectives:
- Understand fundamentals of 3L-NPC and required control objectives (neutral point voltage balance, thermal stress distribution)
- Implement the basic carrier-based control methods for 3L-NPC
- Implement the model predictive control methods for 3L-NPC
- Understand how control selection affects the reliability of components in the 3L-NPC
- Practical design considerations for NPC converters
Teaching methods: Lectures, Excercise, Presentations
Form of evaluation: Students are required to solve exercises using the knowledge acquired in the course and submit a short project report with solutions within three weeks after the course, which will be assessed by the lecturers.
Criteria for assessment: Completed exercises (2) submitted as a short report
Remarks: In total about 46 hours (Preparation: 12 hours, Lecture: 16 hours, Exercise and final report: 18 hours)
Key literature: TBA
Organizer: Frede Blaabjerg, fbl@energy.aau.dk
Lecturers:
Assistant Prof. Ariya Sangwongwanich
Assistant Prof. Mateja Novak
External lecturers: Radu Dan Lazar, Reserach Engineer, Danfoss Drives
ECTS: 2.0
Time: 25 and 26 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 20
Deadline: 4 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Frede Blaabjerg
- Teacher: Radu Lazar
- Teacher: Mateja Novak
- Teacher: Ariya Sangwongwanich
Welcome to Advanced Optimization and Control in Power and Energy Systems (2025)
Description: In the rapidly evolving landscape of power and energy systems, the integration of dispersed generation and renewable energies poses significant challenges and opportunities. Modern energy systems require innovative approaches to control, optimization, and management to ensure reliability, efficiency, and sustainability. This course offers a comprehensive exploration of these challenges and opportunities, equipping participants with the knowledge and skills necessary to navigate and innovate within this dynamic field. Through a series of lectures, hands-on sessions, and discussions, participants will delve into various aspects of modern energy systems, from regulatory frameworks to advanced optimization techniques. The course is designed to address the operational challenges of today's energy systems and develop innovative control and management strategies.
The following topics are covered in the course:
• Challenges in Modern Energy Systems
• Regulatory Frameworks, Grid Codes, Standards, and EU Directives
• Smart Grid Architecture Model (SGAM)
• Hierarchical Control in Energy Systems
• Optimization Techniques (Basic to Advanced)
• Risk Modeling and Management in Energy Systems
• Flexibility Provision in Energy Systems (Electric Vehicles, Heat Pumps, Demand Response)
• Energy Management Systems and Application Examples
• Operation Management in Energy Communities and Grid Interaction Perspectives
• Hands-on Practical Sessions
Key words: Optimization, Energy management, Energy distribution, Flexibility, Control and Operation, Smart grid
Prerequisites: Familiarity with basics of power systems operations, mathematical modelling, and Programming skills.
Learning objectives: By the end of this course, participants will be able to:
- Understand and address modern energy system challenges (i.e., identify operational challenges and opportunities related to dispersed generation and renewable energies),
- Navigate and apply regulatory frameworks (i.e., understand grid codes, standards, and EU directives impacting energy systems),
- Implement advanced control and optimization techniques (i.e., apply hierarchical control strategies, optimization methods, and software tools like gams and matlab for energy management),
- Utilize advanced algorithms to solve complex energy management problems and address uncertainties.
- Develop flexible and resilient energy systems (i.e, enhance system flexibility through the integration of electric vehicles, heat pumps, and demand response programs),
- Design and manage effective energy management systems (i.e., implement robust energy management systems and strategies for operation within energy communities, supported by practical, hands-on experience.)
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: Mini project with a report after the course (deadline is 3 weeks after the course ends)
Criteria for assessment: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project at the end of the course.
Remarks: In total about 98 hours (3.5x28h) hours (20 hours teaching, 5 hours practicing, 15 hours for preparations, 58 for doing the assignment and finalizing a student report)
Key literature: TBA
Organizer:
Prof. Birgitte Bak-Jensen, bbj@energy.aau.dk
Associate Prof. Amjad Anvari-Moghaddam, aam@energy.aau.dk
Assistant Prof. Najmeh Bazmohammadi, naj@energy.aau.dk
Lecturers:
Prof. Birgitte Bak-Jensen, AAU Energy
Associate Prof. Florin Iov, AAU Energy
Associate Prof. Amjad Anvari-Moghaddam, AAU Energy
Assistant Prof. Najmeh Bazmohammadi, AAU Energy
External lecturers:
Prof. Behnam Mohammadi-ivatloo, Lappeenranta-Lahti University of Technology
Prof. Javier Contreras Sanz, Universidad de Castilla-La Mancha
ECTS: 3.5
Time: 15, 16, 17, and 18 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 25 August 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: In the rapidly evolving landscape of power and energy systems, the integration of dispersed generation and renewable energies poses significant challenges and opportunities. Modern energy systems require innovative approaches to control, optimization, and management to ensure reliability, efficiency, and sustainability. This course offers a comprehensive exploration of these challenges and opportunities, equipping participants with the knowledge and skills necessary to navigate and innovate within this dynamic field. Through a series of lectures, hands-on sessions, and discussions, participants will delve into various aspects of modern energy systems, from regulatory frameworks to advanced optimization techniques. The course is designed to address the operational challenges of today's energy systems and develop innovative control and management strategies.
The following topics are covered in the course:
• Challenges in Modern Energy Systems
• Regulatory Frameworks, Grid Codes, Standards, and EU Directives
• Smart Grid Architecture Model (SGAM)
• Hierarchical Control in Energy Systems
• Optimization Techniques (Basic to Advanced)
• Risk Modeling and Management in Energy Systems
• Flexibility Provision in Energy Systems (Electric Vehicles, Heat Pumps, Demand Response)
• Energy Management Systems and Application Examples
• Operation Management in Energy Communities and Grid Interaction Perspectives
• Hands-on Practical Sessions
Key words: Optimization, Energy management, Energy distribution, Flexibility, Control and Operation, Smart grid
Prerequisites: Familiarity with basics of power systems operations, mathematical modelling, and Programming skills.
Learning objectives: By the end of this course, participants will be able to:
- Understand and address modern energy system challenges (i.e., identify operational challenges and opportunities related to dispersed generation and renewable energies),
- Navigate and apply regulatory frameworks (i.e., understand grid codes, standards, and EU directives impacting energy systems),
- Implement advanced control and optimization techniques (i.e., apply hierarchical control strategies, optimization methods, and software tools like gams and matlab for energy management),
- Utilize advanced algorithms to solve complex energy management problems and address uncertainties.
- Develop flexible and resilient energy systems (i.e, enhance system flexibility through the integration of electric vehicles, heat pumps, and demand response programs),
- Design and manage effective energy management systems (i.e., implement robust energy management systems and strategies for operation within energy communities, supported by practical, hands-on experience.)
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: Mini project with a report after the course (deadline is 3 weeks after the course ends)
Criteria for assessment: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project at the end of the course.
Remarks: In total about 98 hours (3.5x28h) hours (20 hours teaching, 5 hours practicing, 15 hours for preparations, 58 for doing the assignment and finalizing a student report)
Key literature: TBA
Organizer:
Prof. Birgitte Bak-Jensen, bbj@energy.aau.dk
Associate Prof. Amjad Anvari-Moghaddam, aam@energy.aau.dk
Assistant Prof. Najmeh Bazmohammadi, naj@energy.aau.dk
Lecturers:
Prof. Birgitte Bak-Jensen, AAU Energy
Associate Prof. Florin Iov, AAU Energy
Associate Prof. Amjad Anvari-Moghaddam, AAU Energy
Assistant Prof. Najmeh Bazmohammadi, AAU Energy
External lecturers:
Prof. Behnam Mohammadi-ivatloo, Lappeenranta-Lahti University of Technology
Prof. Javier Contreras Sanz, Universidad de Castilla-La Mancha
ECTS: 3.5
Time: 15, 16, 17, and 18 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 25 August 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Amjad Anvari-Moghaddam
- Teacher: Birgitte Bak-Jensen
- Teacher: Najmeh Bazmohammadi
- Teacher: Florin Iov
Welcome to Cybersecurity for Microgrids (2025)
Description:
Background:
Microgrids are becoming a cornerstone of power distributions systems that will facilitate the realization of a carbon-neutral electric power systems. Alongside their flexibility to be operated in both grid-connected and autonomous modes, they also provide natural interfaces with many types of RES and ESSs and good compliance with consumer electronics. Moreover, microgrids can be grid-interactive by providing grid supportive functions such as frequency response and, regulation, reactive power support and voltage regulation, etc.
Motivation:
These concerns lead to more and more deployment of microgrids in transmission and distribution levels. Furthermore, with proliferation of communication technologies, microgrids are evolving into cyber-physical systems (CPS) that use sophisticated software-based networked control. This increased sophistication imposes numerous new challenges involving coordination, operation philosophy and vulnerability to cyber-attacks. Cyber-attacks can be designed in many ways: (a) sensor infiltration, (b) communication infringement. Even though several hard-bound secure protocols are designed to ensure the authenticity of the actual signal, the attackers usually target the control layer as an easy target.
Hence, this course aims to focus on:
(a) identifying the vulnerable access points in microgrid controllers
(b) introducing the most prominent cyber-attacks
(c) detection of cyber-attacks in real-time
(d) removal of these attack elements and ensuring stability/preventing system shutdown
(e) various stability issues in microgrids due to cyber-attacks
(f) design of cyber-attack resilient controllers for microgrids, which heals by itself despite any cyber intrusion attempts. Experimental lab demonstration is expected as well along with discussion on future research ideas.
Key words: Cybersecurity, Power Electronics, Microgrids, Information Theory, Control Theory, Signal Processing
Prerequisites: MSc in Power Electronics and Drives, Electric Power Systems, Mechatronics, Wind Power Systems, Wireless Communications
Learning objectives: This course will provide with:
1. a basic understanding of cyber-physical vulnerabilities and their evolution in the recent past
2. defense mechanisms to protect industrial control systems (ICS) and hardware against illegitimate threats
3. non-invasive probing techniques to understand the impact of such threats in ICS and various power electronic applications, such as solar farm, EVs, data centers.
Teaching methods: Lectures, Group work, Excercise, Small assignments
Form of evaluation: The participants will be grouped into teams based on several case studies, data (from our labs) and tasks proposed along the course. Based on the data and lectures, a design challenge (3 exercises) will be conducted to assess the efficacy and robustness of the security design by each team. This will be the terms of assessment for each team in combination with delivery of lab exercise reports.
Criteria for assessment: Efficacy, robustness and simplicity (computational burden, resources) of the security design by each team
Remarks: In total around 38 hours (15 hours teaching, 3 hours for practicing, 3 hours for preparation, 15 hours for finalizing a student report - 3 exercises in a team (max 4 members), 2 hours for exam
Key literature: TBA
Organizer: Subham Sahoo, sssa@energy.aau.dk
Lecturers: Subham Sahoo, sssa@energy.aau.dk
ECTS: 1.5
Time: 10, 11, and 12 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 20 August 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description:
Background:
Microgrids are becoming a cornerstone of power distributions systems that will facilitate the realization of a carbon-neutral electric power systems. Alongside their flexibility to be operated in both grid-connected and autonomous modes, they also provide natural interfaces with many types of RES and ESSs and good compliance with consumer electronics. Moreover, microgrids can be grid-interactive by providing grid supportive functions such as frequency response and, regulation, reactive power support and voltage regulation, etc.
Motivation:
These concerns lead to more and more deployment of microgrids in transmission and distribution levels. Furthermore, with proliferation of communication technologies, microgrids are evolving into cyber-physical systems (CPS) that use sophisticated software-based networked control. This increased sophistication imposes numerous new challenges involving coordination, operation philosophy and vulnerability to cyber-attacks. Cyber-attacks can be designed in many ways: (a) sensor infiltration, (b) communication infringement. Even though several hard-bound secure protocols are designed to ensure the authenticity of the actual signal, the attackers usually target the control layer as an easy target.
Hence, this course aims to focus on:
(a) identifying the vulnerable access points in microgrid controllers
(b) introducing the most prominent cyber-attacks
(c) detection of cyber-attacks in real-time
(d) removal of these attack elements and ensuring stability/preventing system shutdown
(e) various stability issues in microgrids due to cyber-attacks
(f) design of cyber-attack resilient controllers for microgrids, which heals by itself despite any cyber intrusion attempts. Experimental lab demonstration is expected as well along with discussion on future research ideas.
Key words: Cybersecurity, Power Electronics, Microgrids, Information Theory, Control Theory, Signal Processing
Prerequisites: MSc in Power Electronics and Drives, Electric Power Systems, Mechatronics, Wind Power Systems, Wireless Communications
Learning objectives: This course will provide with:
1. a basic understanding of cyber-physical vulnerabilities and their evolution in the recent past
2. defense mechanisms to protect industrial control systems (ICS) and hardware against illegitimate threats
3. non-invasive probing techniques to understand the impact of such threats in ICS and various power electronic applications, such as solar farm, EVs, data centers.
Teaching methods: Lectures, Group work, Excercise, Small assignments
Form of evaluation: The participants will be grouped into teams based on several case studies, data (from our labs) and tasks proposed along the course. Based on the data and lectures, a design challenge (3 exercises) will be conducted to assess the efficacy and robustness of the security design by each team. This will be the terms of assessment for each team in combination with delivery of lab exercise reports.
Criteria for assessment: Efficacy, robustness and simplicity (computational burden, resources) of the security design by each team
Remarks: In total around 38 hours (15 hours teaching, 3 hours for practicing, 3 hours for preparation, 15 hours for finalizing a student report - 3 exercises in a team (max 4 members), 2 hours for exam
Key literature: TBA
Organizer: Subham Sahoo, sssa@energy.aau.dk
Lecturers: Subham Sahoo, sssa@energy.aau.dk
ECTS: 1.5
Time: 10, 11, and 12 September 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 20 August 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Subham Sahoo
Welcome to Catalysis for Renewable Energy: Advances and Applications in Heterogeneous Catalysis (2025)
Description: This course provides a comprehensive exploration of heterogeneous catalysis with a focus on its critical role in renewable energy technologies. Participants will delve into the principles of catalyst preparation, characterization, and reaction mechanisms, learning how these processes are applied in key areas such as biomass conversion, hydrogen production, and CO2 utilization. The course also addresses the pressing need for more efficient and sustainable catalytic processes, driven by the global energy transition towards greener technologies. While the primary focus is on the fundamentals and applications of catalysis, the course will also introduce the use of Artificial Intelligence (AI) as a powerful tool to optimize catalytic processes and accelerate research. Through case studies, exercises, and analysis of current research, participants will gain valuable insights into the challenges and future directions in the field of heterogeneous catalysis for renewable energy solutions.
Key words: Catalyst Preparation & Characterization, Catalytic Mechanisms, Biomass Conversion, CO2 Conversion, Hydrogen Production, and Artificial Intelligence (AI)
Prerequisites: Basic knowledge of chemistry, chemical engineering, and materials science, preferably at the graduate level.
Learning objectives:
By the end of this course, students will be able to:
- Explain the fundamental principles of heterogeneous catalysis, including catalytic mechanisms, types of catalysts, and their specific roles in renewable energy applications. AAC
- Apply advanced techniques for the preparation and characterization of heterogeneous catalysts, such as Transmission Electron Microscopy (TEM), X-ray Photoelectron Spectroscopy (XPS), and Brunauer-Emmett-Teller (BET) surface area analysis. AAC
- Assess the performance and effectiveness of catalytic processes used in renewable energy technologies, including biomass conversion, hydrogen production, CO2 capture and conversion, and the integration of AI in catalytic processes.
- Develop and propose innovative solutions and improvements for catalytic processes, addressing current challenges and leveraging recent advancements in the field.
- Integrate knowledge from theoretical and practical aspects of catalysis to solve complex problems and design research experiments related to renewable energy.
- Reflect on current research trends, identify emerging areas of interest, and critically analyze case studies to inform future research directions and strategies in heterogeneous catalysis for sustainable energy.
- Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation:
The course evaluation will be based on the following components (TBD):
- Group Mini-Report: Students will collaborate in groups to produce a mini-report that addresses a specific challenge in heterogeneous catalysis for renewable energy, incorporating AI-driven approaches where applicable.
- Peer Assessment: Students will evaluate each other’s contributions within the group to ensure accountability and engagement.
- Individual Reflection: Each student will submit a brief reflection on what they learned during the course, including their insights into the use of AI in catalysis and how they might apply this knowledge in their future research.
Criteria for assessment: Pass/not pass
Remarks: In total about 75 hours: 50 teaching and practicing, 10 hours for preparations, 15 hours for participant report.
Key literature: TBA
Organizer: Assistant Professor: Abdenour Achour aac@energy.aau.dk.
Lecturers:
Assistant Professor, Abdenour Achour, AAU Energy,
Deniele Castelo, Associate Professor, AAU Energy,
Vincenzo Liso, Associate Professor, AAU Energy,
Assistant Professor, Kamaldeep Sharma, AAU Energy.
ECTS: 3.0
Time: 6, 7 and 8 October 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 15
Deadline: 15 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: This course provides a comprehensive exploration of heterogeneous catalysis with a focus on its critical role in renewable energy technologies. Participants will delve into the principles of catalyst preparation, characterization, and reaction mechanisms, learning how these processes are applied in key areas such as biomass conversion, hydrogen production, and CO2 utilization. The course also addresses the pressing need for more efficient and sustainable catalytic processes, driven by the global energy transition towards greener technologies. While the primary focus is on the fundamentals and applications of catalysis, the course will also introduce the use of Artificial Intelligence (AI) as a powerful tool to optimize catalytic processes and accelerate research. Through case studies, exercises, and analysis of current research, participants will gain valuable insights into the challenges and future directions in the field of heterogeneous catalysis for renewable energy solutions.
Key words: Catalyst Preparation & Characterization, Catalytic Mechanisms, Biomass Conversion, CO2 Conversion, Hydrogen Production, and Artificial Intelligence (AI)
Prerequisites: Basic knowledge of chemistry, chemical engineering, and materials science, preferably at the graduate level.
Learning objectives:
By the end of this course, students will be able to:
- Explain the fundamental principles of heterogeneous catalysis, including catalytic mechanisms, types of catalysts, and their specific roles in renewable energy applications. AAC
- Apply advanced techniques for the preparation and characterization of heterogeneous catalysts, such as Transmission Electron Microscopy (TEM), X-ray Photoelectron Spectroscopy (XPS), and Brunauer-Emmett-Teller (BET) surface area analysis. AAC
- Assess the performance and effectiveness of catalytic processes used in renewable energy technologies, including biomass conversion, hydrogen production, CO2 capture and conversion, and the integration of AI in catalytic processes.
- Develop and propose innovative solutions and improvements for catalytic processes, addressing current challenges and leveraging recent advancements in the field.
- Integrate knowledge from theoretical and practical aspects of catalysis to solve complex problems and design research experiments related to renewable energy.
- Reflect on current research trends, identify emerging areas of interest, and critically analyze case studies to inform future research directions and strategies in heterogeneous catalysis for sustainable energy.
- Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation:
The course evaluation will be based on the following components (TBD):
- Group Mini-Report: Students will collaborate in groups to produce a mini-report that addresses a specific challenge in heterogeneous catalysis for renewable energy, incorporating AI-driven approaches where applicable.
- Peer Assessment: Students will evaluate each other’s contributions within the group to ensure accountability and engagement.
- Individual Reflection: Each student will submit a brief reflection on what they learned during the course, including their insights into the use of AI in catalysis and how they might apply this knowledge in their future research.
Criteria for assessment: Pass/not pass
Remarks: In total about 75 hours: 50 teaching and practicing, 10 hours for preparations, 15 hours for participant report.
Key literature: TBA
Organizer: Assistant Professor: Abdenour Achour aac@energy.aau.dk.
Lecturers:
Assistant Professor, Abdenour Achour, AAU Energy,
Deniele Castelo, Associate Professor, AAU Energy,
Vincenzo Liso, Associate Professor, AAU Energy,
Assistant Professor, Kamaldeep Sharma, AAU Energy.
ECTS: 3.0
Time: 6, 7 and 8 October 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 15
Deadline: 15 September 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Abdenour Achour
- Teacher: Vincenzo Liso
- Teacher: Kamaldeep Sharma
Welcome to Advanced Computational Fluid Dynamics (2025)
Description: Computational Fluid Dynamics (CFD) has been successfully used for improved understanding, trouble shooting, innovations of technologies and facilities in numerous areas such as energy, mechanical, environmental, health, chemical, food, and pharmaceutical industry. This advanced CFD course will provide a familiarity with and an in-depth understanding of fundamentals of CFD, turbulence modelling, multiphase flow modelling, reacting flow modelling, and user-defined functions and expressions, focusing on the common knowledge behind the overwhelming majority of the commercial, open-source, and in-house CFD codes/tools.
Key words: Fundamentals of CFD; Turbulence modeling; Multiphase flow modeling; Reacting flow modeling; User-defined functions & expressions;
Prerequisites: Basic knowledge in fluid flow, turbulence, multiphase flow, chemical reactions, and programming.
Learning objectives:
1. To provide a familiarity with and an in-depth understanding of (1) the finite volume method, (2) turbulent flows and Reynolds-averaged Navier-Stokes turbulence modelling approach, (3) multiphase flows and flows through porous media, and their modelling, (4) turbulent reacting flows and their modelling, and (5) user-defined functions & expressions and their implementations.
2. To understand and follow more sophisticated state-of-the-art literature in the relevant fields, to be able to develop his or her own CFD codes using FVM to solve simple problems, and to begin advanced applications of CFD to his or her areas of concern.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise, hands-on
Form of evaluation: Finish a mini-project and submit the mini-project report.
Criteria for assessment: Attendance, and mini-project report
Remarks: 120 hours (incl. 30 hours for previewing lecture materials, 30 hours for attending the 4-day lectures, 30 hours for reviewing lecture materials, and 30 hours for completing the mini-project & the corresponding project report)
Key literature: TBA
Organizer: Associate Professor, Chungen Yin, chy@energy.aau.dk
Lecturers:
Associate Professor Chungen Yin, AAU Energy: teaching 3 days
Associate Professor Torsten Berning, AAU Energy: teaching 1 day
Post-Doc Tianbao Gu, AAU Energy: teaching 1-2 lectures
ECTS: 4.0
Time: 18. 19, 20 and 21 August 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 28 July 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: Computational Fluid Dynamics (CFD) has been successfully used for improved understanding, trouble shooting, innovations of technologies and facilities in numerous areas such as energy, mechanical, environmental, health, chemical, food, and pharmaceutical industry. This advanced CFD course will provide a familiarity with and an in-depth understanding of fundamentals of CFD, turbulence modelling, multiphase flow modelling, reacting flow modelling, and user-defined functions and expressions, focusing on the common knowledge behind the overwhelming majority of the commercial, open-source, and in-house CFD codes/tools.
Key words: Fundamentals of CFD; Turbulence modeling; Multiphase flow modeling; Reacting flow modeling; User-defined functions & expressions;
Prerequisites: Basic knowledge in fluid flow, turbulence, multiphase flow, chemical reactions, and programming.
Learning objectives:
1. To provide a familiarity with and an in-depth understanding of (1) the finite volume method, (2) turbulent flows and Reynolds-averaged Navier-Stokes turbulence modelling approach, (3) multiphase flows and flows through porous media, and their modelling, (4) turbulent reacting flows and their modelling, and (5) user-defined functions & expressions and their implementations.
2. To understand and follow more sophisticated state-of-the-art literature in the relevant fields, to be able to develop his or her own CFD codes using FVM to solve simple problems, and to begin advanced applications of CFD to his or her areas of concern.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise, hands-on
Form of evaluation: Finish a mini-project and submit the mini-project report.
Criteria for assessment: Attendance, and mini-project report
Remarks: 120 hours (incl. 30 hours for previewing lecture materials, 30 hours for attending the 4-day lectures, 30 hours for reviewing lecture materials, and 30 hours for completing the mini-project & the corresponding project report)
Key literature: TBA
Organizer: Associate Professor, Chungen Yin, chy@energy.aau.dk
Lecturers:
Associate Professor Chungen Yin, AAU Energy: teaching 3 days
Associate Professor Torsten Berning, AAU Energy: teaching 1 day
Post-Doc Tianbao Gu, AAU Energy: teaching 1-2 lectures
ECTS: 4.0
Time: 18. 19, 20 and 21 August 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 28 July 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Torsten Berning
- Teacher: Tianbao Gu
- Teacher: Chungen Yin
Welcome to Energy Storage Systems: Techno-Economic Aspects, Control Mechanisms, and Grid Integration (2025)
Description: This intensive four-day course offers a comprehensive and advanced exploration of energy storage systems, emphasizing their critical role in modern power grids. As power systems increasingly integrate renewable energy sources and demand for reliable, efficient, and sustainable energy grows, energy storage systems are becoming indispensable. This course is meticulously designed to provide participants with a thorough understanding of the key components and technologies that drive energy storage systems, focusing on their integration into power grids.
Day 1: Overview of Energy Storage Technologies and Battery Modeling
The course begins with a comprehensive overview of energy storage technologies, delving into their various characteristics, such as energy density, efficiency, and lifecycle, and examining their crucial roles within power systems. Participants will explore how different storage technologies contribute to enhancing grid stability, accommodating renewable energy integration, and supporting critical services such as frequency control and voltage regulation. The day continues with an in-depth exploration of Battery Energy Storage Systems (BESS), including battery pack modeling. This session will cover the structural and functional dynamics of battery packs, focusing on challenges like cell balancing and performance optimization. The day concludes with a hands-on lab session where participants will use MATLAB and Python tools to simulate battery pack models and test balancing algorithms.
Day 2: Market Dynamics, Regulations, and Grid Applications of Energy Storage
The second day of the course is dedicated to exploring both the economic and technical aspects of energy storage systems within the context of power grids. The morning session delves into the market dynamics of energy storage, including cost structures, pricing mechanisms, and the economic value of services provided by storage systems. Participants will also explore the regulatory environment, including policies, standards, and guidelines that impact the deployment and operation of energy storage technologies. The afternoon session discusses the critical role of energy storage in power grids, with a focus on how these systems contribute to frequency control and voltage support, ensuring grid stability and reliability. This is followed by a detailed exploration of the design factors and modeling techniques that influence the performance of energy storage systems. A practical session using MATLAB/Simulink will allow participants to apply these concepts in simulated environments.
Day 3: Control Methods and Power Electronics in Energy Storage Systems
Day three is dedicated to the advanced study of control methods and power electronics in energy storage systems. The morning begins with a thorough examination of control methods, particularly those used for frequency regulation and maintaining grid stability. Following this, participants will delve into power electronic converters, exploring their design principles and the critical role they play in integrating energy storage systems with the grid. The afternoon session will focus on control strategies for power electronic converters, including real-world applications and dynamic responses to grid conditions. The day concludes with a practical session where participants will apply control techniques using MATLAB/Simulink.
Day 4: Real-Time Simulation and Project Integration
The final day introduces participants to real-time simulation and testing of energy storage systems. The morning session will cover OPAL-RT, a state-of-the-art real-time simulator used for power systems and energy storage simulations, and the PHIL platform, which integrates physical hardware with real-time simulation for testing and validation. In the afternoon, participants will be introduced to the final project, which involves integrating concepts learned throughout the course.
Key words: Energy Storage Systems, Battery Modeling, Power Electronics, Grid Integration, Frequency Control, Real-Time Simulation
Prerequisites: Fundamental understanding in power systems, power electronics, and familiar with control theory. Experience in using Matlab/Simulink
Learning objectives:
- Gain comprehensive knowledge of various energy storage technologies and their roles in power systems.
- Develop advanced skills in battery modeling, including pack structure, balancing circuits, and performance optimization.
- Master control strategies for energy storage systems, with a particular focus on frequency regulation and stability.
- Understand the design and control of power electronic converters essential for integrating energy storage systems with the grid.
- Explore the economic, regulatory, and policy frameworks that impact energy storage deployment.
- Integrate and apply theoretical knowledge in real-world scenarios using hands-on experience with MATLAB, Python, and OPAL-RT tools.
Teaching methods: Lectures, Small assignments, Excercise, Group work, Presentations
Form of evaluation: Participants will be assessed through a series of exercises and a final report submission.
Criteria for assessment: Exercises: Relevance and Accuracy: The ability to correctly apply course concepts in the completion of exercises. Problem-Solving: Demonstration of effective problem-solving skills and the ability to address the practical challenges posed in the exercises. Final Report Submission: Depth of Analysis: The final report should showcase a comprehensive understanding of the course material, with in-depth analysis and application of key concepts. Clarity and Organization: The report should be well-structured, clearly written, and logically organized, with a coherent argument and thorough explanation of the chosen topic. Application of Knowledge: The report should effectively apply theoretical knowledge to a practical scenario or case study, demonstrating the participant's ability to integrate and synthesize the course content.
Remarks:
- Teaching: 28.5 hours
- Practice (Labs/Projects): 8 hours
- Preparation: 12 hours
- Final Project/Report: 8 hours
- Examination (Quiz and Report): 4.5 hours
- Total: 61 hours (equivalent to 3 ECTS)
- Key literature: TBA
Organizer: Prof. Remus Teodorescu (ret@energy.aau.dk) and Asst. Prof. Arman Oshnoei (aros@energy.aau.dk)
Lecturers:
Prof. Remus Teodorescu, Aalborg University
Asst. Prof. Arman Oshnoei, Aalborg University
PhD researchers, Aalborg University.
External lecturers: Assoc. Prof. Amin Mahmoudi, Flinders University, Adelaide, Australia.
ECTS: 3.0
Time: 10 - 13 June 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 20 May 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: This intensive four-day course offers a comprehensive and advanced exploration of energy storage systems, emphasizing their critical role in modern power grids. As power systems increasingly integrate renewable energy sources and demand for reliable, efficient, and sustainable energy grows, energy storage systems are becoming indispensable. This course is meticulously designed to provide participants with a thorough understanding of the key components and technologies that drive energy storage systems, focusing on their integration into power grids.
Day 1: Overview of Energy Storage Technologies and Battery Modeling
The course begins with a comprehensive overview of energy storage technologies, delving into their various characteristics, such as energy density, efficiency, and lifecycle, and examining their crucial roles within power systems. Participants will explore how different storage technologies contribute to enhancing grid stability, accommodating renewable energy integration, and supporting critical services such as frequency control and voltage regulation. The day continues with an in-depth exploration of Battery Energy Storage Systems (BESS), including battery pack modeling. This session will cover the structural and functional dynamics of battery packs, focusing on challenges like cell balancing and performance optimization. The day concludes with a hands-on lab session where participants will use MATLAB and Python tools to simulate battery pack models and test balancing algorithms.
Day 2: Market Dynamics, Regulations, and Grid Applications of Energy Storage
The second day of the course is dedicated to exploring both the economic and technical aspects of energy storage systems within the context of power grids. The morning session delves into the market dynamics of energy storage, including cost structures, pricing mechanisms, and the economic value of services provided by storage systems. Participants will also explore the regulatory environment, including policies, standards, and guidelines that impact the deployment and operation of energy storage technologies. The afternoon session discusses the critical role of energy storage in power grids, with a focus on how these systems contribute to frequency control and voltage support, ensuring grid stability and reliability. This is followed by a detailed exploration of the design factors and modeling techniques that influence the performance of energy storage systems. A practical session using MATLAB/Simulink will allow participants to apply these concepts in simulated environments.
Day 3: Control Methods and Power Electronics in Energy Storage Systems
Day three is dedicated to the advanced study of control methods and power electronics in energy storage systems. The morning begins with a thorough examination of control methods, particularly those used for frequency regulation and maintaining grid stability. Following this, participants will delve into power electronic converters, exploring their design principles and the critical role they play in integrating energy storage systems with the grid. The afternoon session will focus on control strategies for power electronic converters, including real-world applications and dynamic responses to grid conditions. The day concludes with a practical session where participants will apply control techniques using MATLAB/Simulink.
Day 4: Real-Time Simulation and Project Integration
The final day introduces participants to real-time simulation and testing of energy storage systems. The morning session will cover OPAL-RT, a state-of-the-art real-time simulator used for power systems and energy storage simulations, and the PHIL platform, which integrates physical hardware with real-time simulation for testing and validation. In the afternoon, participants will be introduced to the final project, which involves integrating concepts learned throughout the course.
Key words: Energy Storage Systems, Battery Modeling, Power Electronics, Grid Integration, Frequency Control, Real-Time Simulation
Prerequisites: Fundamental understanding in power systems, power electronics, and familiar with control theory. Experience in using Matlab/Simulink
Learning objectives:
- Gain comprehensive knowledge of various energy storage technologies and their roles in power systems.
- Develop advanced skills in battery modeling, including pack structure, balancing circuits, and performance optimization.
- Master control strategies for energy storage systems, with a particular focus on frequency regulation and stability.
- Understand the design and control of power electronic converters essential for integrating energy storage systems with the grid.
- Explore the economic, regulatory, and policy frameworks that impact energy storage deployment.
- Integrate and apply theoretical knowledge in real-world scenarios using hands-on experience with MATLAB, Python, and OPAL-RT tools.
Teaching methods: Lectures, Small assignments, Excercise, Group work, Presentations
Form of evaluation: Participants will be assessed through a series of exercises and a final report submission.
Criteria for assessment: Exercises: Relevance and Accuracy: The ability to correctly apply course concepts in the completion of exercises. Problem-Solving: Demonstration of effective problem-solving skills and the ability to address the practical challenges posed in the exercises. Final Report Submission: Depth of Analysis: The final report should showcase a comprehensive understanding of the course material, with in-depth analysis and application of key concepts. Clarity and Organization: The report should be well-structured, clearly written, and logically organized, with a coherent argument and thorough explanation of the chosen topic. Application of Knowledge: The report should effectively apply theoretical knowledge to a practical scenario or case study, demonstrating the participant's ability to integrate and synthesize the course content.
Remarks:
- Teaching: 28.5 hours
- Practice (Labs/Projects): 8 hours
- Preparation: 12 hours
- Final Project/Report: 8 hours
- Examination (Quiz and Report): 4.5 hours
- Total: 61 hours (equivalent to 3 ECTS)
- Key literature: TBA
Organizer: Prof. Remus Teodorescu (ret@energy.aau.dk) and Asst. Prof. Arman Oshnoei (aros@energy.aau.dk)
Lecturers:
Prof. Remus Teodorescu, Aalborg University
Asst. Prof. Arman Oshnoei, Aalborg University
PhD researchers, Aalborg University.
External lecturers: Assoc. Prof. Amin Mahmoudi, Flinders University, Adelaide, Australia.
ECTS: 3.0
Time: 10 - 13 June 2025
Place: Aalborg University, AAU Energy (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 20 May 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Arman Oshnoei
- Teacher: Remus Teodorescu
Welcome to Reliability of Power Electronic based Power Systems (PEPS) (2025)
Description: Modern power electric based power systems (PEPS) are facing new challenges in terms of reliable planning and operation due to proliferation of power electronic converters. The course is aimed at providing an in-depth introduction to the reliability modeling, assessment and enhancement approaches in PEPS. The basic principles of reliability evaluation along with their application, current practices and solution methods in PEPS will be discussed.
Key words: Reliability of power electronics, stress-strength analysis, design for reliability, wear-out failure, Ansys, Number of cycles to failure, maintenance
Prerequisites: The participant must have knowledge and competences like the level of an engineer with a MSc in power electronics, probability and control of power electronics converters. The relevant topics of reliability will be provided as pre-read documents and will be covered during teaching.
Learning objectives:
1. Fundamental concepts of reliability Engineering
2. Structural reliability and stress strength analysis
3. Introduction to converter reliability prediction
4. Impacts of converter control on PEPS reliability
5. Reliability modeling in PEPS
6. Model-based design for reliability in PEPS
7. Model-based maintenance scheduling in PPES
8. Reliability enhancement in PEPS
9. Challenges and opportunities
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: Active engagement during the course and report on the two mini projects.
Criteria for assessment: Active engagement during the course and report on the mini projects.
Remarks: In total about 56 hours (26 hours teaching and practicing, 10 hours for preparations, 20 hours for finalizing a student report and XX (TBA) hours for examination)
Key literature: TBA
Organizer: Associate Professor Saeed Peyghami, sap@energy.aau.dk
Lecturers:
Associate Professor Saeed Peyghami sap@energy.aau.dk
Postdoc Seyed Amir Hosseini saho@energy.aau.dk
ECTS: 2.0
Time: 23 - 24 June 2025
Place: Aalborg University, AAU Energy in Aalborg and Online (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 40
Deadline: 2 June 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: Modern power electric based power systems (PEPS) are facing new challenges in terms of reliable planning and operation due to proliferation of power electronic converters. The course is aimed at providing an in-depth introduction to the reliability modeling, assessment and enhancement approaches in PEPS. The basic principles of reliability evaluation along with their application, current practices and solution methods in PEPS will be discussed.
Key words: Reliability of power electronics, stress-strength analysis, design for reliability, wear-out failure, Ansys, Number of cycles to failure, maintenance
Prerequisites: The participant must have knowledge and competences like the level of an engineer with a MSc in power electronics, probability and control of power electronics converters. The relevant topics of reliability will be provided as pre-read documents and will be covered during teaching.
Learning objectives:
1. Fundamental concepts of reliability Engineering
2. Structural reliability and stress strength analysis
3. Introduction to converter reliability prediction
4. Impacts of converter control on PEPS reliability
5. Reliability modeling in PEPS
6. Model-based design for reliability in PEPS
7. Model-based maintenance scheduling in PPES
8. Reliability enhancement in PEPS
9. Challenges and opportunities
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: Active engagement during the course and report on the two mini projects.
Criteria for assessment: Active engagement during the course and report on the mini projects.
Remarks: In total about 56 hours (26 hours teaching and practicing, 10 hours for preparations, 20 hours for finalizing a student report and XX (TBA) hours for examination)
Key literature: TBA
Organizer: Associate Professor Saeed Peyghami, sap@energy.aau.dk
Lecturers:
Associate Professor Saeed Peyghami sap@energy.aau.dk
Postdoc Seyed Amir Hosseini saho@energy.aau.dk
ECTS: 2.0
Time: 23 - 24 June 2025
Place: Aalborg University, AAU Energy in Aalborg and Online (Room: TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 40
Deadline: 2 June 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Seyed Amir Hosseini
- Teacher: Saeed Peyghami
Welcome to Reliability Assesment in Electric Power Systems (2025)
Description: The course on Reliability in Electric Power Systems focuses on ensuring a stable and continuous supply of electricity in increasingly complex power systems. As we integrate more renewable energy sources and advanced technologies, maintaining system reliability becomes essential. This course covers the basics of reliability, the impact of different system components, and the latest methods for assessing and improving reliability. Participants will gain practical skills to handle real-world challenges, ensuring power systems run smoothly and meet regulatory standards.
Key words: Markov Process, Availability, Capacity Outage Probability Table (COPT), Loss of Load Expectation (LOLE), Excepted Power not Supplied (EENS), System Average Interruption Frequency Index (SAIFI)
Prerequisites:
In a course on reliability in electric power systems, probability and statistics are crucial for analyzing the power system behavior. Although these concepts will be covered during the course, it is helpful to have a basic understanding beforehand.
This includes fundamental probability theory—such as sample spaces, events, and probability measures—as well as knowledge of random variables for modeling different events in power systems. Additionally, an initial review of common probability distributions (e.g., normal, exponential, binomial) and their applications will aid in understanding how to model system components and failures more effectively.
Learning objectives:
Welcome to Reliability Assesment in Electric Power Systems (2025)
Description: The course on Reliability in Electric Power Systems focuses on ensuring a stable and continuous supply of electricity in increasingly complex power systems. As we integrate more renewable energy sources and advanced technologies, maintaining system reliability becomes essential. This course covers the basics of reliability, the impact of different system components, and the latest methods for assessing and improving reliability. Participants will gain practical skills to handle real-world challenges, ensuring power systems run smoothly and meet regulatory standards.
Key words: Markov Process, Availability, Capacity Outage Probability Table (COPT), Loss of Load Expectation (LOLE), Excepted Power not Supplied (EENS), System Average Interruption Frequency Index (SAIFI)
Prerequisites:
In a course on reliability in electric power systems, probability and statistics are crucial for analyzing the power system behavior. Although these concepts will be covered during the course, it is helpful to have a basic understanding beforehand.
This includes fundamental probability theory—such as sample spaces, events, and probability measures—as well as knowledge of random variables for modeling different events in power systems. Additionally, an initial review of common probability distributions (e.g., normal, exponential, binomial) and their applications will aid in understanding how to model system components and failures more effectively.
Learning objectives:
- Understanding the fundamental of system reliability engineering
- Understanding the concepts of power system reliability
- Exposure to probabilistic technique applications to power system problems
- Exposure to reliability cost/worth problem and investigating the tradeoff between reliability and economics
Teaching methods: Lectures, Group work, Small assignments, Excercise, Presentations
Form of evaluation: The course is evaluated by a report on two mini projects.
Criteria for assessment: Assessment is based on the combination of active engagement during the course and the project reports.
Remarks: In total about 95 hours (60 teaching and practicing, 15 hours for preparations, 20 for finalizing a student report)
Key literature: TBA
Organizer:
Prof. Frede Blaabjerg, fbl@energy.aau.dk
Associate Prof. Saeed Peyghami, sap@energy.aau.dk
Postdoc. Seyed Amir Hosseini, saho@energy.aau.dk
Lecturers:
Prof. Frede Blaabjerg, fbl@energy.aau.dk
Associate Prof. Saeed Peyghami, sap@energy.aau.dk
Postdoc. Seyed Amir Hosseini, saho@energy.aau.dk
ECTS: 4.0
Time: 16 - 19 June 2025
Place: Aalborg University, AAU Energy in Aalborg and Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 40
Deadline: 26 May 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: The course on Reliability in Electric Power Systems focuses on ensuring a stable and continuous supply of electricity in increasingly complex power systems. As we integrate more renewable energy sources and advanced technologies, maintaining system reliability becomes essential. This course covers the basics of reliability, the impact of different system components, and the latest methods for assessing and improving reliability. Participants will gain practical skills to handle real-world challenges, ensuring power systems run smoothly and meet regulatory standards.
Key words: Markov Process, Availability, Capacity Outage Probability Table (COPT), Loss of Load Expectation (LOLE), Excepted Power not Supplied (EENS), System Average Interruption Frequency Index (SAIFI)
Prerequisites:
In a course on reliability in electric power systems, probability and statistics are crucial for analyzing the power system behavior. Although these concepts will be covered during the course, it is helpful to have a basic understanding beforehand.
This includes fundamental probability theory—such as sample spaces, events, and probability measures—as well as knowledge of random variables for modeling different events in power systems. Additionally, an initial review of common probability distributions (e.g., normal, exponential, binomial) and their applications will aid in understanding how to model system components and failures more effectively.
Learning objectives:
Welcome to Reliability Assesment in Electric Power Systems (2025)
Description: The course on Reliability in Electric Power Systems focuses on ensuring a stable and continuous supply of electricity in increasingly complex power systems. As we integrate more renewable energy sources and advanced technologies, maintaining system reliability becomes essential. This course covers the basics of reliability, the impact of different system components, and the latest methods for assessing and improving reliability. Participants will gain practical skills to handle real-world challenges, ensuring power systems run smoothly and meet regulatory standards.
Key words: Markov Process, Availability, Capacity Outage Probability Table (COPT), Loss of Load Expectation (LOLE), Excepted Power not Supplied (EENS), System Average Interruption Frequency Index (SAIFI)
Prerequisites:
In a course on reliability in electric power systems, probability and statistics are crucial for analyzing the power system behavior. Although these concepts will be covered during the course, it is helpful to have a basic understanding beforehand.
This includes fundamental probability theory—such as sample spaces, events, and probability measures—as well as knowledge of random variables for modeling different events in power systems. Additionally, an initial review of common probability distributions (e.g., normal, exponential, binomial) and their applications will aid in understanding how to model system components and failures more effectively.
Learning objectives:
- Understanding the fundamental of system reliability engineering
- Understanding the concepts of power system reliability
- Exposure to probabilistic technique applications to power system problems
- Exposure to reliability cost/worth problem and investigating the tradeoff between reliability and economics
Teaching methods: Lectures, Group work, Small assignments, Excercise, Presentations
Form of evaluation: The course is evaluated by a report on two mini projects.
Criteria for assessment: Assessment is based on the combination of active engagement during the course and the project reports.
Remarks: In total about 95 hours (60 teaching and practicing, 15 hours for preparations, 20 for finalizing a student report)
Key literature: TBA
Organizer:
Prof. Frede Blaabjerg, fbl@energy.aau.dk
Associate Prof. Saeed Peyghami, sap@energy.aau.dk
Postdoc. Seyed Amir Hosseini, saho@energy.aau.dk
Lecturers:
Prof. Frede Blaabjerg, fbl@energy.aau.dk
Associate Prof. Saeed Peyghami, sap@energy.aau.dk
Postdoc. Seyed Amir Hosseini, saho@energy.aau.dk
ECTS: 4.0
Time: 16 - 19 June 2025
Place: Aalborg University, AAU Energy in Aalborg and Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 40
Deadline: 26 May 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Frede Blaabjerg
- Teacher: Seyed Amir Hosseini
- Teacher: Saeed Peyghami
Welcome to Microgrids: Modelling, Control, and Energy Management (2025)
Description: A Microgrid can be defined as a part of the grid with distributed energy resources, power electronic converters, distributed energy storage systems, and local loads, that can operate autonomously but also interacting with the main grid. The functionalities expected for these small grids are black start operation, frequency and voltage stability, active and reactive power flow control, active power filter capabilities, and storage and energy management. This way, the energy can be generated and stored near the consumption points, increasing reliability, and reducing the losses produced by the large power lines.
The Microgrids course aims at offering a comprehensive introduction to AC and DC Microgrids, their operating and control challenges, opportunities, and applications. The course participants will learn about advanced modeling, control strategies, and operation management systems for Microgrids in both grid-connected and islanded modes, and for mobile Ad-hoc microgrids, community microgrids, and microgrid clusters. Moreover, stability analysis, advanced grid synchronization techniques, energy management and communication systems, and Internet of Things (IoT)-enabled energy and asset operation managements are explored to ensure efficiency, reliability, and resilience operation of Microgrids.
The key areas that are covered by the course include:
- Microgrid concept, challenges, and requirements.
- Hierarchical control of AC/DC Microgrids.
- Grid-forming and Grid-following Inverters, Frequency and voltage droop control.
- Modeling and stability analysis of Microgrids.
- Virtual synchronize generators.
- Control of Uninterruptible Power Supply (UPS) Systems.
- Advanced grid synchronization systems.
- IoT-enabled Microgrids.
- Energy management system for microgrids and its applications.
- Mobile Ad-hoc microgrids and community microgrids.
- Microgrid clusters control and operation management.
Key words: Microgrids; Hierarchical control; Grid forming and grid following; Grid Synchronization; Energy Management; Power Quality
Prerequisites: Familiarity with basics of power systems operations, mathematical modelling, and programming skills. Basic understanding of classic control theory and familiarity with MATLAB/Simulink. Knowledge on power electronics modelling and control theory is recommended for the exercises.
Learning objectives:
By the end of this course, participants will be able to:
- Understand the Microgrids concept, their challenges, applications, and architectures (AC/DC/hybrid).
- Analyze and simulate modeling and control design of power electronic interfaces AC-AC, AC-DC, DC-DC, and AC-DC for Microgrid specifications.
- Understand and conduct stability analysis for AC and DC Microgrids.
- Analyze and design grid forming and grid following inverters for Microgrids.
- Understand communication technologies and IoT and their applications for monitoring, control, and energy and asset management systems.
- Design and develop advanced grid synchronization techniques, phase-locked loops, and frequency-locked loops, including small signal modeling, control, and analysis.
- Develop advanced energy management systems for microgrids using advanced optimization techniques.
- Develop resilience-oriented control and operation management systems for mobile Ad-hoc and community microgrids.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: The participants will be grouped and asked to work and present multiple case studies during the course including the preparation of a final report to be sent to the lecturers within three weeks after the course.
Criteria for assessment: The participants will be evaluated both individually and in groups during the hands-on sessions over the course period and their final reports.
Remarks: In total about 112 hours (4×28h): 26 hours teaching, 6 hours practicing, 15 hours for preparations, 65 for the assignments and final reporting)
Key literature: TBA
Organizer:
Assoc. Prof. Yajuan Guan
Assist. Prof. Najmeh Bazmohammadi
Lecturers:
Prof. Juan C. Vasquez, juq@energy.aau.dk;
Assoc. Prof. Yajuan Guan, ygu@energy.aau.dk;
Assoc. Prof. Sanjay Chaudhary, skc@energy.aau.dk;
Assoc. Prof. Saeed Golestan, sgd@energy.aau.dk;
Assoc. Prof. Baoze Wei, bao@energy.aau.dk;
Assist. Prof. Najmeh Bazmohammadi, naj@energy.aau.dk;
Postdoc. Ali Akhavan, alak@energy.aau.dk;
Postdoc. Abderezak Lashab, abl@energy.aau.dk;
Postdoc. Babak Arbab Zavar, baz@energy.aau.dk;
Postdoc. Yun Yu, yyu@et.aau.dk;
ECTS: 4.0
Time: 19 - 23 May 2025
Place: Aalborg University, AAU Energy in Aalborg and Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 28 April 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: A Microgrid can be defined as a part of the grid with distributed energy resources, power electronic converters, distributed energy storage systems, and local loads, that can operate autonomously but also interacting with the main grid. The functionalities expected for these small grids are black start operation, frequency and voltage stability, active and reactive power flow control, active power filter capabilities, and storage and energy management. This way, the energy can be generated and stored near the consumption points, increasing reliability, and reducing the losses produced by the large power lines.
The Microgrids course aims at offering a comprehensive introduction to AC and DC Microgrids, their operating and control challenges, opportunities, and applications. The course participants will learn about advanced modeling, control strategies, and operation management systems for Microgrids in both grid-connected and islanded modes, and for mobile Ad-hoc microgrids, community microgrids, and microgrid clusters. Moreover, stability analysis, advanced grid synchronization techniques, energy management and communication systems, and Internet of Things (IoT)-enabled energy and asset operation managements are explored to ensure efficiency, reliability, and resilience operation of Microgrids.
The key areas that are covered by the course include:
- Microgrid concept, challenges, and requirements.
- Hierarchical control of AC/DC Microgrids.
- Grid-forming and Grid-following Inverters, Frequency and voltage droop control.
- Modeling and stability analysis of Microgrids.
- Virtual synchronize generators.
- Control of Uninterruptible Power Supply (UPS) Systems.
- Advanced grid synchronization systems.
- IoT-enabled Microgrids.
- Energy management system for microgrids and its applications.
- Mobile Ad-hoc microgrids and community microgrids.
- Microgrid clusters control and operation management.
Key words: Microgrids; Hierarchical control; Grid forming and grid following; Grid Synchronization; Energy Management; Power Quality
Prerequisites: Familiarity with basics of power systems operations, mathematical modelling, and programming skills. Basic understanding of classic control theory and familiarity with MATLAB/Simulink. Knowledge on power electronics modelling and control theory is recommended for the exercises.
Learning objectives:
By the end of this course, participants will be able to:
- Understand the Microgrids concept, their challenges, applications, and architectures (AC/DC/hybrid).
- Analyze and simulate modeling and control design of power electronic interfaces AC-AC, AC-DC, DC-DC, and AC-DC for Microgrid specifications.
- Understand and conduct stability analysis for AC and DC Microgrids.
- Analyze and design grid forming and grid following inverters for Microgrids.
- Understand communication technologies and IoT and their applications for monitoring, control, and energy and asset management systems.
- Design and develop advanced grid synchronization techniques, phase-locked loops, and frequency-locked loops, including small signal modeling, control, and analysis.
- Develop advanced energy management systems for microgrids using advanced optimization techniques.
- Develop resilience-oriented control and operation management systems for mobile Ad-hoc and community microgrids.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: The participants will be grouped and asked to work and present multiple case studies during the course including the preparation of a final report to be sent to the lecturers within three weeks after the course.
Criteria for assessment: The participants will be evaluated both individually and in groups during the hands-on sessions over the course period and their final reports.
Remarks: In total about 112 hours (4×28h): 26 hours teaching, 6 hours practicing, 15 hours for preparations, 65 for the assignments and final reporting)
Key literature: TBA
Organizer:
Assoc. Prof. Yajuan Guan
Assist. Prof. Najmeh Bazmohammadi
Lecturers:
Prof. Juan C. Vasquez, juq@energy.aau.dk;
Assoc. Prof. Yajuan Guan, ygu@energy.aau.dk;
Assoc. Prof. Sanjay Chaudhary, skc@energy.aau.dk;
Assoc. Prof. Saeed Golestan, sgd@energy.aau.dk;
Assoc. Prof. Baoze Wei, bao@energy.aau.dk;
Assist. Prof. Najmeh Bazmohammadi, naj@energy.aau.dk;
Postdoc. Ali Akhavan, alak@energy.aau.dk;
Postdoc. Abderezak Lashab, abl@energy.aau.dk;
Postdoc. Babak Arbab Zavar, baz@energy.aau.dk;
Postdoc. Yun Yu, yyu@et.aau.dk;
ECTS: 4.0
Time: 19 - 23 May 2025
Place: Aalborg University, AAU Energy in Aalborg and Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 28 April 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Ali Akhavan
- Teacher: Babak Arbab Zavar
- Teacher: Najmeh Bazmohammadi
- Teacher: Sanjay Chaudhary
- Teacher: Saeed Golestan
- Teacher: Yajuan Guan
- Teacher: Abderezak Lashab
- Teacher: Juan C. Vasquez
- Teacher: Baoze Wei
- Teacher: Yun Yu
Welcome to A Model Based Design Approach for Integration of Co-Located Hybrid Plants in Future Energy System (2025)
Description: In order to reach the 2030environmental targets the Danish government aims to increase the installed capacity of renewable generation to 36 GW while installing more than 6 GW installations for hydrogen production. Green ammonia production will also increase significantly in the next years. The expected amount of these new installations poses new challenges to the power grid as its expansion or reinforcement takes usually long periods from approval to commissioning and thus postponing the targets. One of the envisaged solutions is to establish co-located plants with limited grid connection capacity. In this way the renewable energy is produced and consumed locally in a so-called hybrid plant that comprises for examples of wind turbines, solar PV systems and electrolyzers. Batteries will play a crucial role in these installations for maintaining the internal security of supply but also providing grid support functionalities. The Danish transmission system operator have recently launched the first draft of the grid connection requirements for these installations that is expected to enter into force by early 2025. It is believed that a better utilization of plant infrastructure, a steady power output over longer time periods and thus a better grid and market integration will be achieved in a shorter time. However, these new regulations are posing challenges for all expected stakeholders in the value chain. New approaches for design, control and operation of these plant are needed. This five days course is giving a systematic approach for modelling, control design and operation of Hybrid Plants using the Model-Based Design approach. It includes a wide range of hands-on exercises as well as demonstrations in a Real-Time Hardware-In-the Loop framework. The activities and main recommendations of IEA TCP Wind Task 50 and upcoming Task 61 will be included in the course materials as well as invited lectures on selected relevant topics. Lectures are supported by exercises included in assignments that shall be completed by participants. The evaluation is based on a mini report containing the solution of the assignments.
Key words: Hybrid plants, renewable generation, Power-to-X, grid and market integration, control and operation
Prerequisites: Participants must have basic knowledge at MSc level on electrical engineering and control theory. Basic knowledge on Matlab/Simulink including Toolboxes is recommended for completing the assignments.
Learning objectives:
Knowledge:
• Architecture, operational strategies and market integration of hybrid plants comprising of renewable energy sources such as wind and solar PV, energy storage systems and flexible electrical loads e.g. electrolyzers and fuel cells;
• Monitoring, control and interoperability in hybrid power plants
• Comprehension of the electrical aspects of hybrid plants and their analysis under stationary and contingency situations using digital platforms
• Comprehension within operation, control and optimization of hybrid plants using digital platforms
Skills:
• Be able to judge the usefulness of the used different scientific methods for the design of optimisation, control, and/or diagnostic systems for hybrid plants using digital platforms
• Be able to verify the different scientific analysis methods combined with laboratory experiments or real measured data series
Competences:
• Be able to understand current trends and future developments within grid and market integration of hybrid plants
• Be able to identify challenges in control and operation of hybrid plants from different stakeholder prespectives
• Be able to select the appropriate modelling granularity of subcomponents in a hybrid plant for different types of integration studies
Teaching methods: Lectures, Small assignments
Form of evaluation: Individual evaluation of the participants based on submitted report that details the solution of assignments. The mini-report shall be submitted in maximum four weeks after the end of lectures
Criteria for assessment: Pass/Fail criterion. It is required the completion of at least 66% of each assignment in order to pass
Remarks:
Total Hours: 98 hours
30 hours lectures
6 hours for preparation
60 hours for solving 12 assignments and prepare mini-report
2 hours online QA session regarding assignments
Key literature: TBA
Organizer: Associate Professor Florin Iov, fi@energy.aau.dk
Lecturers:
Associated Professor Tamas Kerekes
Associated Professor Daniel-Ioan Stroe
Associated Professor Simon Sahlin
Associated Professor Vincenzo Liso
Associated Professor Rasmus Olsen Løvenstein (Electronic Systems)
ECTS: 3.5
Time: 17 - 20 March 2025
Place: Aalborg University AAU Energy, Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 24 February 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: In order to reach the 2030environmental targets the Danish government aims to increase the installed capacity of renewable generation to 36 GW while installing more than 6 GW installations for hydrogen production. Green ammonia production will also increase significantly in the next years. The expected amount of these new installations poses new challenges to the power grid as its expansion or reinforcement takes usually long periods from approval to commissioning and thus postponing the targets. One of the envisaged solutions is to establish co-located plants with limited grid connection capacity. In this way the renewable energy is produced and consumed locally in a so-called hybrid plant that comprises for examples of wind turbines, solar PV systems and electrolyzers. Batteries will play a crucial role in these installations for maintaining the internal security of supply but also providing grid support functionalities. The Danish transmission system operator have recently launched the first draft of the grid connection requirements for these installations that is expected to enter into force by early 2025. It is believed that a better utilization of plant infrastructure, a steady power output over longer time periods and thus a better grid and market integration will be achieved in a shorter time. However, these new regulations are posing challenges for all expected stakeholders in the value chain. New approaches for design, control and operation of these plant are needed. This five days course is giving a systematic approach for modelling, control design and operation of Hybrid Plants using the Model-Based Design approach. It includes a wide range of hands-on exercises as well as demonstrations in a Real-Time Hardware-In-the Loop framework. The activities and main recommendations of IEA TCP Wind Task 50 and upcoming Task 61 will be included in the course materials as well as invited lectures on selected relevant topics. Lectures are supported by exercises included in assignments that shall be completed by participants. The evaluation is based on a mini report containing the solution of the assignments.
Key words: Hybrid plants, renewable generation, Power-to-X, grid and market integration, control and operation
Prerequisites: Participants must have basic knowledge at MSc level on electrical engineering and control theory. Basic knowledge on Matlab/Simulink including Toolboxes is recommended for completing the assignments.
Learning objectives:
Knowledge:
• Architecture, operational strategies and market integration of hybrid plants comprising of renewable energy sources such as wind and solar PV, energy storage systems and flexible electrical loads e.g. electrolyzers and fuel cells;
• Monitoring, control and interoperability in hybrid power plants
• Comprehension of the electrical aspects of hybrid plants and their analysis under stationary and contingency situations using digital platforms
• Comprehension within operation, control and optimization of hybrid plants using digital platforms
Skills:
• Be able to judge the usefulness of the used different scientific methods for the design of optimisation, control, and/or diagnostic systems for hybrid plants using digital platforms
• Be able to verify the different scientific analysis methods combined with laboratory experiments or real measured data series
Competences:
• Be able to understand current trends and future developments within grid and market integration of hybrid plants
• Be able to identify challenges in control and operation of hybrid plants from different stakeholder prespectives
• Be able to select the appropriate modelling granularity of subcomponents in a hybrid plant for different types of integration studies
Teaching methods: Lectures, Small assignments
Form of evaluation: Individual evaluation of the participants based on submitted report that details the solution of assignments. The mini-report shall be submitted in maximum four weeks after the end of lectures
Criteria for assessment: Pass/Fail criterion. It is required the completion of at least 66% of each assignment in order to pass
Remarks:
Total Hours: 98 hours
30 hours lectures
6 hours for preparation
60 hours for solving 12 assignments and prepare mini-report
2 hours online QA session regarding assignments
Key literature: TBA
Organizer: Associate Professor Florin Iov, fi@energy.aau.dk
Lecturers:
Associated Professor Tamas Kerekes
Associated Professor Daniel-Ioan Stroe
Associated Professor Simon Sahlin
Associated Professor Vincenzo Liso
Associated Professor Rasmus Olsen Løvenstein (Electronic Systems)
ECTS: 3.5
Time: 17 - 20 March 2025
Place: Aalborg University AAU Energy, Online
Zip code: 9220
City: Aalborg
Maximal number of participants: 25
Deadline: 24 February 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Florin Iov
- Teacher: Tamas Kerekes
- Teacher: Vincenzo Liso
- Teacher: Daniel-Ioan Stroe
Welcome to Energy Markets and Analytics (2025)
Description:
Energy markets are at the heart of one of the biggest societal challenges of our time - creating a sustainable, reliable and affordable energy provision. Renewable Energies are also new guests and participants in such markets. The PhD/industrial course on “Energy Markets and Analytics” aims at providing an in depth introduction to energy markets and how the renewable energies can be integrated in them safely. The participants will learn how to implement the concepts using appropriate software packages on planning, decision making and optimization. The course will mainly cover the following subjects:
Day 1 (8:30-16:30)
1.1. Introduction to energy markets
1.2. Pricing and market clearing mechanisms
1.3. Competition and different type of markets
1.4. Market participants
1.5. Challenges of participation of renewable energy resources (RER) in markets
Day 2 (8:30-16:30)
2.1. Policies for integrating RERs in markets around the world
2.2. Impact of RERs on market clearing and market outputs
2.3. Demand side management for RERs integration in energy markets
2.4. Energy storage for RERs integration in energy markets
2.5. Impact of RER on balancing market Prerequisites.
Key words: Energy Markets, Renewable Energy Integration, Market Clearing Mechanisms, Demand Side Management, Energy Storage, Optimization.
Prerequisites: Basics of optimization theory
Learning objectives:
- Gain a comprehensive understanding of energy markets, including pricing, market clearing mechanisms, and types of markets.
- Explore the challenges and opportunities of integrating renewable energy resources (RER) into energy markets.
- Examine global policies for integrating RERs and understand their impact on market operations.
- Learn strategies for demand-side management and the role of energy storage in supporting RER integration.
- Develop skills in using analytical tools and software for planning, decision-making, and optimization in energy markets.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project on market practices at the end of the course.
Criteria for assessment: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project at the end of the course.
Remarks: In total about 42 hours (12 hours teaching, 6 hours practicing, 4 hours for preparations, 20 hours for doing the assignment and finalizing a student report)
Key literature: TBA
Organizer: Associate Professor Amjad Anvari-Moghaddam, aam@energy.aau.dk
Lecturers: Associate Professor Amjad Anvari-Moghaddam, AAU Energy
External lecturers: Professor Behnam Mohammadi-Ivatloo – Lappeenranta-Lahti University of Technology
ECTS: 1.5
Time: 6 - 7 March 2025
Place: Aalborg University, Online course
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 13 February 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description:
Energy markets are at the heart of one of the biggest societal challenges of our time - creating a sustainable, reliable and affordable energy provision. Renewable Energies are also new guests and participants in such markets. The PhD/industrial course on “Energy Markets and Analytics” aims at providing an in depth introduction to energy markets and how the renewable energies can be integrated in them safely. The participants will learn how to implement the concepts using appropriate software packages on planning, decision making and optimization. The course will mainly cover the following subjects:
Day 1 (8:30-16:30)
1.1. Introduction to energy markets
1.2. Pricing and market clearing mechanisms
1.3. Competition and different type of markets
1.4. Market participants
1.5. Challenges of participation of renewable energy resources (RER) in markets
Day 2 (8:30-16:30)
2.1. Policies for integrating RERs in markets around the world
2.2. Impact of RERs on market clearing and market outputs
2.3. Demand side management for RERs integration in energy markets
2.4. Energy storage for RERs integration in energy markets
2.5. Impact of RER on balancing market Prerequisites.
Key words: Energy Markets, Renewable Energy Integration, Market Clearing Mechanisms, Demand Side Management, Energy Storage, Optimization.
Prerequisites: Basics of optimization theory
Learning objectives:
- Gain a comprehensive understanding of energy markets, including pricing, market clearing mechanisms, and types of markets.
- Explore the challenges and opportunities of integrating renewable energy resources (RER) into energy markets.
- Examine global policies for integrating RERs and understand their impact on market operations.
- Learn strategies for demand-side management and the role of energy storage in supporting RER integration.
- Develop skills in using analytical tools and software for planning, decision-making, and optimization in energy markets.
Teaching methods: Lectures, Group work, Presentations, Small assignments, Excercise
Form of evaluation: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project on market practices at the end of the course.
Criteria for assessment: The participants will be evaluated by exercises on a daily basis (both individually and in groups) and a mini-project at the end of the course.
Remarks: In total about 42 hours (12 hours teaching, 6 hours practicing, 4 hours for preparations, 20 hours for doing the assignment and finalizing a student report)
Key literature: TBA
Organizer: Associate Professor Amjad Anvari-Moghaddam, aam@energy.aau.dk
Lecturers: Associate Professor Amjad Anvari-Moghaddam, AAU Energy
External lecturers: Professor Behnam Mohammadi-Ivatloo – Lappeenranta-Lahti University of Technology
ECTS: 1.5
Time: 6 - 7 March 2025
Place: Aalborg University, Online course
Zip code: 9220
City: Aalborg
Maximal number of participants: 30
Deadline: 13 February 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Amjad Anvari-Moghaddam
- Teacher: Behnam Mohammadiivatloo
Welcome to Grid-Forming Converters: Principles and Practices (2025)
Description: Converter-based systems dominate modern grids due to increasing renewables, where grid-forming controlled converters play a key role in maintaining power system stability. This course addresses crucial grid-forming converter principles, including grid codes, control design, stability, resonance damping, and fault management for power professionals and researchers.
Key words: Grid-forming converters, grid codes, control, modeling, stability, fault
Prerequisites: Basic knowledge in ac circuits, power electronic converters and control theories.
Learning objectives: Concepts of grid-forming converters, grid code requirements for grid-forming, detailed control structures, simple control implementation in simulations and stability analysis
Teaching methods: Lectures
Form of evaluation: Mini report
Criteria for assessment: A report that solves the exercise
Remarks: 16 hours for teaching, 2 hours for practicing on the courses, 10 hours for reviewing the lectures, 36 hours for investigating the exercise, and 20 hours for finalizing the report.
Key literature: TBA
Organizer: Professor Xiongfei Wang, xwa@energy.aau.dk.
Lecturers:
Professor Xiongfei Wang, Aalborg University.
Assistent Professor Heng Wu, Aalborg University
Assistent Professor Fangzhou Zhao, Aalborg University
External Lecturers:
Dr. Pedro Rodriguez, Luxembourg Institute of Science and Technology (LIST)
ECTS: 3.0
Time: 17, 18, 19 februar 2025
Place: Aalborg University AAU Energy (Room TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 50
Deadline: 27 January 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
Description: Converter-based systems dominate modern grids due to increasing renewables, where grid-forming controlled converters play a key role in maintaining power system stability. This course addresses crucial grid-forming converter principles, including grid codes, control design, stability, resonance damping, and fault management for power professionals and researchers.
Key words: Grid-forming converters, grid codes, control, modeling, stability, fault
Prerequisites: Basic knowledge in ac circuits, power electronic converters and control theories.
Learning objectives: Concepts of grid-forming converters, grid code requirements for grid-forming, detailed control structures, simple control implementation in simulations and stability analysis
Teaching methods: Lectures
Form of evaluation: Mini report
Criteria for assessment: A report that solves the exercise
Remarks: 16 hours for teaching, 2 hours for practicing on the courses, 10 hours for reviewing the lectures, 36 hours for investigating the exercise, and 20 hours for finalizing the report.
Key literature: TBA
Organizer: Professor Xiongfei Wang, xwa@energy.aau.dk.
Lecturers:
Professor Xiongfei Wang, Aalborg University.
Assistent Professor Heng Wu, Aalborg University
Assistent Professor Fangzhou Zhao, Aalborg University
External Lecturers:
Dr. Pedro Rodriguez, Luxembourg Institute of Science and Technology (LIST)
ECTS: 3.0
Time: 17, 18, 19 februar 2025
Place: Aalborg University AAU Energy (Room TBA)
Zip code: 9220
City: Aalborg
Maximal number of participants: 50
Deadline: 27 January 2025
Important information concerning PhD courses:
There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.
We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.
To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.
For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration at aauphd@adm.aau.dk When contacting us please state the course title and course period. Thank you.
- Teacher: Xiongfei Wang
- Teacher: Heng Wu
- Teacher: Fangzhou Zhao