Description:
A Microgrid can be defined as a part of the grid with elements of prime energy movers, power electronics converters, distributed energy storage systems and local loads, that can operate autonomously but also interacting with 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 energy management. This way, the energy can be generated and stored near the consumption points, increasing the reliability and reducing the losses produced by the large power lines.
The course starts giving some examples of microgrids in the world. The course participants not only will learn modeling, simulation and control of three-phase voltage source inverters operating in grid-connected mode and islanded mode, but also, how these power electronics converters are integrated in both AC and DC microgrids. Relevant concepts like frequency and voltage droop control as well as the virtual impedance concept are explained in detail. This course also introduces the study of the hierarchical control of microgrids for AC electrical distribution systems.
Prerequisites: Matlab/Simulink knowledge is recommended for the exercises.

Organizer:
Professor Josep M. Guerrero, joz@et.aau.dk, Aalborg University

Lecturers:
Professor Remus Teodorescu, Professor Josep M. Guerrero, Assistant Professor Juan C. Vasquez, PhD Student Dan Wu, Professor Mukul Chandorkar, IIT, India.

ECTS:
3

Time:
23-24 September 2013

Place:
Aalborg University, Pontoppidanstræde 101, room 19

Zip code:
9220

City:
Aalborg

Number of seats:
30

Deadline:
9 September 2013

Important information concerning PhD courses
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to AC Microgrids

Description: A Microgrid can be defined as a part of the grid with elements of prime energy movers, power electronics converters, distributed energy storage systems and local loads, that can operate autonomously but also interacting with 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 energy management. This way, the energy can be generated and stored near the consumption points, increasing the reliability and reducing the losses produced by the large power lines.

The course starts giving some examples of Microgrids in the world. The course participants not only will learn modeling, simulation and control of three-phase voltage source inverters operating in grid-connected mode and islanded mode, but also, how these power electronics converters are integrated in AC Microgrids.

Relevant concepts like frequency and voltage droop control as well as the virtual impedance concept are explained in detail. Finally, this course also introduces the study of the hierarchical control of Microgrids for AC electrical distribution systems.

Prerequisites: Matlab/Simulink knowledge is recommended for the exercises.

Organizer: Associate Professor Juan C. Vasquez, Aalborg University, email: juq@et.aau.dk and Professor Josep M. Guerrero, Aalborg University, email: joz@et.aau.dk

Lecturers: Professor Josep M. Guerrero, Aalborg University, Associate Professor Juan C. Vasquez, Aalborg University, Professor Ernane Coelho, Unidersidade Federal de Uberlândia - Brazil, Postdoc Yajuan Guan, Aalvorg University

ECTS: 2

Price: 6000 DKK for PhD students outside of Denmark and 1500 DKK for PhD students in Denmark, who are not from AAU. 8000 DKK for the Industry.

Time: 24. - 25. April 2017

Place:

Zip code:

City:

Number of seats: 20

Deadline: 3. April 2017

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Relevant concepts like frequency and voltage droop control as well as the virtual impedance concept are explained in detail. Finally, this course also introduces the study of the hierarchical control of Microgrids for AC electrical distribution systems, stability analysis based on small signal models, as well as Energy Internet-enabled opportunities and advanced solutions.  

Description:  A Microgrid can be defined as a part of the grid with elements of prime energy movers, power electronics converters, distributed energy storage systems and local loads, that can operate autonomously but also interacting with 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 energy management. This way, the energy can be generated and stored near the consumption points, increasing the reliability, and reducing the losses produced by the large power lines. In addition, as one of current trends and developments the Internet of Things (IoT) is affecting and will shape the society and the world in all respects. The meet of IoT and energy industry naturally brings the promise of Energy Internet round the corner to introduce significant advantages and opportunities: enhanced automation, controllability, interoperability and energy efficiency, smarter energy management, and so on. The course starts giving some examples of Microgrids in the world. The course participants not only will learn modeling, simulation and advanced control strategies of three-phase voltage source inverters operating in grid-connected mode and islanded mode, but also, how these power electronics converters are integrated in AC Microgrids and how to be extended Energy Internet at a systemic level.

Relevant concepts like frequency and voltage droop control, virtual impedance, UPS, virtual synchronize generator concept are explained in detail. Finally, this course also introduces the study of the hierarchical control of Microgrids for AC electrical distribution systems, stability analysis based on small signal models, communication technologies in AC microgrids, and Energy Internet-enabled opportunities and advanced solutions.

Day 1:  Microgrids Systems Overview, Modelling, Grid forming and Grid Feeding Control, Hierarchical Control

Josep Guerrero (3h), Yajuan Guan (3h), Yun Yu (1h)

Day 2: Stability Analysis, Passivity-based modelling, Power Flow Analysis and lab. demonstration

Josep Guerrero (1h), Yajuan Guan (3h), Ali Akhavan (2h), David Tinajero (1h)

Day 3: Virtual Synchorous generators, Industrial Microgrid applications, communications and IoT in Microgrids

Juan Vasquez (1h), Yajuan Guan (2h), Baoze Wei (1h), Babak Arbab Zavar (1h), Ying Wu (2h)

Prerequisites:

Knowledge on power electronics modelling, control theory and Matlab/Simulink is recommended for the exercises.

Form of evaluation:

The participants will be grouped and asked to team work on several case study scenarios and tasks proposed along the course. The course assessment will be done through a final multi-choice test in combination with delivery of exercises reports.

Organizer:     Profesor Juan C. Vasquez, juq@energy.aau.dk, Professor Josep M. Guerrero, joz@energy.aau.dk

Lecturers:      Profesor Josep M. Guerrero, Aalborg University,Profesor Juan C. Vasquez, Aalborg University, Assoc. Professor, Yajuan Guan, Aalborg University

                       Assistant Professor, Baoze Wei, Aalborg University, Assistant Professor Gibran Tinajero, Aalborg University, Postdoc, Ying Wu, Aalborg University

                       Postdoc, Ali Akhavan, Aalborg University, Babak Arbab Zavar, Aalborg University

ECTS:              3

Date/Time:     April 3 -5, 2023

Place:              AAU Energy, Aalborg

Max no. of participants:    25

Deadline:       13 March 2023

Literature:

1.       Book chapters:

1.1.     Chapter 1 & 2 of Microgrids: Modeling, Control, and Applications (Elsevier)

2.       Articles

2.1.     J. M. Guerrero, J. Matas, L. Garcia de Vicuna, M. Castilla and J. Miret, "Decentralized Control for Parallel Operation of Distributed Generation Inverters Using Resistive Output Impedance," in IEEE Transactions on Industrial Electronics, vol. 54, no. 2, pp. 994-1004, April 2007, doi: 10.1109/TIE.2007.892621.

2.2.     J. M. Guerrero, J. C. Vasquez, J. Matas, M. Castilla and L. Garcia de Vicuna, "Control Strategy for Flexible Microgrid Based on Parallel Line-Interactive UPS Systems," in IEEE Transactions on Industrial Electronics, vol. 56, no. 3, pp. 726-736, March 2009, doi: 10.1109/TIE.2008.2009274.

2.3.     J. M. Guerrero, L. Hang and J. Uceda, "Control of Distributed Uninterruptible Power Supply Systems," in IEEE Transactions on Industrial Electronics, vol. 55, no. 8, pp. 2845-2859, Aug. 2008, doi: 10.1109/TIE.2008.924173.

2.4.     J. C. Vasquez, J. M. Guerrero, M. Savaghebi, J. Eloy-Garcia and R. Teodorescu, "Modeling, Analysis, and Design of Stationary-Reference-Frame Droop-Controlled Parallel Three-Phase Voltage Source Inverters," in IEEE Transactions on Industrial Electronics, vol. 60, no. 4, pp. 1271-1280, April 2013, doi: 10.1109/TIE.2012.2194951.

2.5.     Y. Han, H. Li, P. Shen, E. A. A. Coelho and J. M. Guerrero, "Review of Active and Reactive Power Sharing Strategies in Hierarchical Controlled Microgrids," in IEEE Transactions on Power Electronics, vol. 32, no. 3, pp. 2427-2451, March 2017, doi: 10.1109/TPEL.2016.2569597.

2.6.     J. C. Vasquez, J. M. Guerrero, J. Miret, M. Castilla and L. G. de Vicuña, "Hierarchical Control of Intelligent Microgrids," in IEEE Industrial Electronics Magazine, vol. 4, no. 4, pp. 23-29, Dec. 2010, doi: 10.1109/MIE.2010.938720.

2.7.     J. M. Guerrero, J. C. Vasquez, J. Matas, L. G. de Vicuna and M. Castilla, "Hierarchical Control of Droop-Controlled AC and DC Microgrids—A General Approach Toward Standardization," in IEEE Transactions on Industrial Electronics, vol. 58, no. 1, pp. 158-172, Jan. 2011, doi: 10.1109/TIE.2010.2066534.

2.8.     J. M. Guerrero, M. Chandorkar, T. -L. Lee and P. C. Loh, "Advanced Control Architectures for Intelligent Microgrids—Part I: Decentralized and Hierarchical Control," in IEEE Transactions on Industrial Electronics, vol. 60, no. 4, pp. 1254-1262, April 2013, doi: 10.1109/TIE.2012.2194969.

2.9.     J. M. Guerrero, P. C. Loh, T. -L. Lee and M. Chandorkar, "Advanced Control Architectures for Intelligent Microgrids—Part II: Power Quality, Energy Storage, and AC/DC Microgrids," in IEEE Transactions on Industrial Electronics, vol. 60, no. 4, pp. 1263-1270, April 2013, doi: 10.1109/TIE.2012.2196889.

2.10. Q. Shafiee, J. M. Guerrero and J. C. Vasquez, "Distributed Secondary Control for Islanded Microgrids—A Novel Approach," in IEEE Transactions on Power Electronics, vol. 29, no. 2, pp. 1018-1031, Feb. 2014, doi: 10.1109/TPEL.2013.2259506.

2.11. Y. Guan, J. M. Guerrero, X. Zhao, J. C. Vasquez and X. Guo, "A New Way of Controlling Parallel-Connected Inverters by Using Synchronous-Reference-Frame Virtual Impedance Loop—Part I: Control Principle," in IEEE Transactions on Power Electronics, vol. 31, no. 6, pp. 4576-4593, June 2016, doi: 10.1109/TPEL.2015.2472279.

2.12. Y. Guan, J. C. Vasquez, J. M. Guerrero and E. A. A. Coelho, "Small-signal modeling, analysis and testing of parallel three-phase-inverters with a novel autonomous current sharing controller," 2015 IEEE Applied Power Electronics Conference and Exposition (APEC), 2015, pp. 571-578, doi: 10.1109/APEC.2015.7104406.

2.13. Y. Guan, J. C. Vasquez and J. M. Guerrero, "An enhanced hierarchical control strategy for the Internet of Things-based home scale microgrid," 2017 IEEE 26th International Symposium on Industrial Electronics (ISIE), 2017, pp. 51-56, doi: 10.1109/ISIE.2017.8001222.

2.14. B. Wei, J. M. Guerrero, J. C. Vásquez and X. Guo, "A Circulating-Current Suppression Method for Parallel-Connected Voltage-Source Inverters With Common DC and AC Buses," in IEEE Transactions on Industry Applications, vol. 53, no. 4, pp. 3758-3769, July-Aug. 2017, doi: 10.1109/TIA.2017.2681620.

2.15. B. Wei, A. Marzàbal, R. Ruiz, J. M. Guerrero and J. C. Vasquez, "DAVIC: A New Distributed Adaptive Virtual Impedance Control for Parallel-Connected Voltage Source Inverters in Modular UPS System," in IEEE Transactions on Power Electronics, vol. 34, no. 6, pp. 5953-5968, June 2019, doi: 10.1109/TPEL.2018.2869870.

2.16. B. Wei, Y. Gui, S. Trujillo, J. M. Guerrero, J. C. Vásquez and A. Marzàbal, "Distributed Average Integral Secondary Control for Modular UPS Systems-Based Microgrids," in IEEE Transactions on Power Electronics, vol. 34, no. 7, pp. 6922-6936, July 2019, doi: 10.1109/TPEL.2018.2873793.

2.17. B. Wei, A. Marzàbal, J. Perez, R. Pinyol, J. M. Guerrero and J. C. Vásquez, "Overload and Short-Circuit Protection Strategy for Voltage Source Inverter-Based UPS," in IEEE Transactions on Power Electronics, vol. 34, no. 11, pp. 11371-11382, Nov. 2019, doi: 10.1109/TPEL.2019.2898165.

2.18. Babak Arbab-Zavar, Emilio J. Palacios-Garcia, Juan C. Vasquez, Josep M. Guerrero, "LoRa Enabled Smart Inverters for Microgrid Scenarios with Widespread Elements," in Electronics, 2021, 10(21), 2680; https://doi.org/10.3390/electronics10212680.

2.19. E. J. Palacios-Garcia, B. Arbab-Zavar, J. C. Vasquez and J. M. Guerrero, "Open IoT Infrastructures for In-Home Energy Management and Control," 2019 IEEE 9th International Conference on Consumer Electronics (ICCE-Berlin), 2019, pp. 376-379, doi: 10.1109/ICCE-Berlin47944.2019.8966225.

2.20. Babak Arbab-Zavar, Suleiman M. Sharkh, Emilio J. Palacios-Garcia, Juan C. Vasquez, Josep M. Guerrero, "Reducing Detrimental Communication Failure Impacts in Microgrids by Using Deep Learning Techniques," Sensors, 2022, 22(16), 6006; https://doi.org/10.3390/s22166006.

2.21. Y. Yu et al., "A Reference-Feedforward-Based Damping Method for Virtual Synchronous Generator Control," in IEEE Transactions on Power Electronics, vol. 37, no. 7, pp. 7566-7571, July 2022, doi: 10.1109/TPEL.2022.3152358.

2.22. Y. Yu, S. K. Chaudhary, S. Golestan, G. D. A. Tinajero, J. C. Vasquez and J. M. Guerrero, "An Overview of Grid-Forming Control for Wind Turbine Converters," IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021, pp. 1-6, doi: 10.1109/IECON48115.2021.9589838.

2.23. Y. Yu et al., "A Comparison of Fixed-Parameter Active-Power-Oscillation Damping Solutions for Virtual Synchronous Generators," IECON 2021 – 47th Annual Conference of the IEEE Industrial Electronics Society, 2021, pp. 1-6, doi: 10.1109/IECON48115.2021.9589433.

2.24. Q. -C. Zhong, P. -L. Nguyen, Z. Ma and W. Sheng, "Self-Synchronized Synchronverters: Inverters Without a Dedicated Synchronization Unit," in IEEE Transactions on Power Electronics, vol. 29, no. 2, pp. 617-630, Feb. 2014, doi: 10.1109/TPEL.2013.2258684.

2.25. T. Shintai, Y. Miura and T. Ise, "Oscillation Damping of a Distributed Generator Using a Virtual Synchronous Generator," in IEEE Transactions on Power Delivery, vol. 29, no. 2, pp. 668-676, April 2014, doi: 10.1109/TPWRD.2013.2281359.

2.26. S. Wang, J. Hu and X. Yuan, "Virtual Synchronous Control for Grid-Connected DFIG-Based Wind Turbines," in IEEE Journal of Emerging and Selected Topics in Power Electronics, vol. 3, no. 4, pp. 932-944, Dec. 2015, doi: 10.1109/JESTPE.2015.2418200.

2.27. Lashab, D. Sera, J. Martins and J. M. Guerrero, "Dual-Input Quasi-Z-Source PV Inverter: Dynamic Modeling, Design, and Control," in IEEE Transactions on Industrial Electronics, vol. 67, no. 8, pp. 6483-6493, Aug. 2020, doi: 10.1109/TIE.2019.2935927.

2.28. Lashab, D. Sera, F. Hahn, L. Juarez Camurca, M. Liserre and J. M. Guerrero, "A Reduced Power Switches Count Multilevel Converter-Based Photovoltaic System With Integrated Energy Storage," in IEEE Transactions on Industrial Electronics, vol. 68, no. 9, pp. 8231-8240, Sept. 2021, doi: 10.1109/TIE.2020.3009594.

3.       Presentations

3.1.     Microgrid as a way of life by Prof. Josep M Guerrero https://www.youtube.com/watch?v=T-y8rW6oQq8

4.       Laboratory introduction Handbook (provided via Moodle)

Welcome to Active Fault-Tolerant Control: Theory and Applications
 

Description: A Fault Tolerant Control (FTC) system is referred to a controlled system that poses the capability to accommodate system component faults/failures automatically and is capable of maintaining overall system stability and acceptable performance in the event of such faults. In general, the FTC capability can be possibly achieved through passive or active approaches. The passiv FTC is limited by the nominal control system’s robustness, while the active FTC approach often consists of two integrated online functionalities, i.e., Fault Detection and Diagnosis (FDD) and Control Reconfiguration (CR). Thereby, the active FTC is also regarded as a kind of intelligent control solution.

The FTC plays an essential rule in safe-critical systems, which now cover a wide range of engineering systems, from aircrafts, airspace systems and nuclear reactors, to the recent emerging energy systems, such as smart grid systems, offshore wind farms etc. The ultimate objective of applying FTC techniques is to cost-effectively increase engineering system’s reliability, safety availability and maintainability.

The course covers the fundamental essentials and some latest results in FTC research area, along with diverse application case studies. The main content consists of: Historical and technical overview & terminology; FDD techniques (data-driven & model-based); CR techniques (model-matching & modelfollowing): Integration of FDD and CR: fundamental FDD/FTC property analysis and diverse case studies.

The course will be evaluated based on a mini-project after the course. This mini-project expects some illustration that the student can apply some techniques/knowledge learned from this course into their current PhD project.

Literatures:

Lecture notes/slides will be provided and the following two books are recommended:

• Jie Chen and R. Patton, "Robust model-based fault diagnosis for dynamic Systems", Kluwer, Boston, 1999.
• R. Isermann, "Fault-diagnosis systems: An introduction from fault detection to fault tolerant", Springer, 2006. ISBN 3-540-24112-4.

Prerequisites: Basic knowledge of control theory (incl. state-space methods)

Organizer: Associate Professor Zhenyu Yang, email: yang@et.aau.dk, Aalborg University

Lecturers: Associate Professor Zhenyu Yang, Aalborg University, Dr. Jie Chen, Brunel

University, UK

ECTS: 4

Price: 6000 DKK for PhD students outside of Denmark and 1500 DKK for PhD students in Denmark, who are not from AAU. 8000 DKK for the Industry.

Time: 20- 24 March 2017

Place: Aalborg University, Esbjerg Campus, Niels Bohrs Vej 8

Zip code: 6700

City: Esbjerg

Number of seats: 30

Deadline: 27 February 2017

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Organiser: Associate Professor Zhenyu Yang, AAU Energy

Lecturers: Professor Roozbeh Izadi-Zamanabadi, Dept of Electronics Systems, AAU and Associate Professor Zhenyu Yang, AAU Energy, AAU

ECTS: 4.0

Date: week 20, 13 May – 17 May 2024

Place: Aalborg University Esbjerg, Niels Bohrs Vej 8, 6700 Esbjerg

Price: 6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT. A link for the payment by credit card will be announced efter deadline for registration.

Deadline: 22 April 2024

Format: hybrid (online & in person)

Max no. of participants: 30

As a part-time Professor at AAU, Dr. Izadi-Zamanabadi is also a Lead Control Expert at Danfoss A/S. He has over 30 years research and development experiences on FDD and FTC, as well as applications of advanced FDD and FTC in diverse industrial systems.

Dr. Yang has over 30 years research and development experiences in the FDD and FTC areas, including both traditional model-based methods and data-driven learning methods.

Description: A Fault Tolerant Control (FTC) system is referred to a controlled system that poses the capability to accommodate system component faults/failures automatically and is capable of maintaining overall system stability and acceptable performance in the event of such faults. An active FTC approach often consists of two integrated online functionalities, i.e., Fault Detection and Diagnosis (FDD) and Control Reconfiguration (CR). The FTC plays an essential rule in safe-critical systems, which now cover a wide range of engineering systems, from aircrafts, airspace systems and nuclear reactors, to the recent emerging energy systems, such as smart grid systems, offshore wind farms etc. The ultimate objective of applying FTC techniques is to cost-effectively increase engineering system’s reliability, safety availability and maintainability. This course covered the fundamental essentials and some latest results in active FTC research area, along with diverse application case studies. The course daily plan consists of about 4-hour lectures and 2-hour exercises every day, such as;

• Day 1: Introduction & State-estimation-based FDD 
• Day 2: FMEA and Structual Analysis (SA) method
• Day 3: Data-driven modeling and FTC methods 
• Day 4: Unknown input observer & Machine-learning based FDD methods 
• Day 5: Advanced FTC design & applications 
  
  

Prerequisites: The participants need to have the fundamental knowledge about classical control theory (transfer-function based) and modern control theory (state-space based).

Find more information about the course here

Description:
Digital controllers are now extremely powerful. With the current Field Programmable Gate Array (FPGA), designing a controller is no longer limited to the programming of a microprocessor but includes also the programming of the architecture of the processor itself along with its peripherals and its computing accelerators. As a consequence, the control designer should be now a system architect who also needs a deep understanding of the final system to be controlled. Along this line, this course aims to propose a rational use of current FPGA-based reconfigurable platforms for controlling power electronic and drive applications. 

The following topics are covered in the course: 

Organizers:
Professor Josep M. Guerrero, joz@energy.aau.dk  
Professor Juan C. Vasquez, juq@energy.aau.dk  

Lecturers:
Professor Eric Monmasson, University of Cergy-Pontoise 
Assistant Professor Mattia Ricco, University of Bologna 

ECTS: 3

Time: 11-13 April 2022

Place: AAU Energy, Aalborg

Number of seats: 15

Price: 6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT

Deadline: 21 March 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to AI for the People

Description: The notion of Artificial Intelligence (AI) dates back approx. 70 years as a research field and even longer if one considers fiction writers. A number of different definitions of AI has been suggested over the years, but none seem to capture what AI is. This might be due to the fact that AI is about computer algorithms that behave intelligently. And since the capabilities of computer algorithms improve over time, no static definition is possible.

One aspect of AI is the ability to learn or adapt dynamically. This concept has inspired numerous Sci-fi books and movies with the underlying theme of man vs AI (often manifested in a robot). From this follows naturally ethical and regulatory considerations. But until recently, such considerations (see for example the three Robotic laws defined by the sci-fi writer I. Asimov) have been speculative since current AI algorithms (and their manifestation in mechanical devices) have performed poorly and hence never left university labs around the world. Recently, however, fast hardware and massive amount of data have allowed revisiting one particular AI algorithm invented in the 80s, namely Artificial Neural Networks (ANN), and increasing the size of the networks used in these models. This was exemplified via image processing for recognizing hand-written digits and resulted in amazing results. Inspired by this success ANN (now known as Deep Learning (DL)) was quickly picked up by other research fields where similar successes have been witnessed.

DL algorithms can now outperform humans on a number of tasks. Moreover, they can, to a certain degree, learn new tasks. An important point in this regard is that the algorithm is so complex that it is next to impossible to understand its inner workings. So, we seem to be facing a reality where AI, in a not too distant future, will be used to make decisions (simply because it is of better than humans). This raises a number of ethical and regulative questions such as, for instance, 1) how we ensure that AI systems are not discriminating against certain groups in the population, 2) how do we ensure transparency about the decisions made by AI systems, and relatedly 3) could and should individuals be given a substantial right to an explanation of decisions made by such systems and a substantial right not to be subjected to automated decision-making (GDPR). Since many of the currently developed AI systems operate on the basis of large amounts of data, the development and use of such systems also reinvigorate the ethical issues related to ‘Big data’. Finally, there are problems related to the efficacy and safety of AI systems. This raises questions not only of how appropriate monitoring of the development of these systems can be secured, but also and more importantly about the appropriate domains for use.

These questions and related questions are the core focus of the PhD course on ‘AI for the people’. The aim is to raise an awareness in the participants. To this end the course will be a combination of lectures, debates and an assignment, and includes the following topics:

• Introduction to AI
• Ethical issues in the development and use of AI
• Industry perspective on AI

Prerequisites: None - besides an open mind and interest in AI and how it is affecting society and individuals.

Enrolment, details and information: 

https://phd.moodle.aau.dk/course/view.php?id=2485 - October

Welcome to AI for the People 

Description: The notion of Artificial Intelligence (AI) dates back approx. 70 years as a research field and even longer if one considers fiction writers. A number of different definitions of AI has been suggested over the years, but none seem to capture what AI is. This might be due to the fact that AI is about computer algorithms that behave intelligently. And since the capabilities of computer algorithms improve over time, no static definition is possible.

One aspect of AI is the ability to learn or adapt dynamically. This concept has inspired numerous Sci-fi books and movies with the underlying theme of man vs AI (often manifested in a robot). From this follows naturally ethical and regulatory considerations. But until recently, such considerations (see for example the three Robotic laws defined by the sci-fi writer I. Asimov) have been speculative since current AI algorithms (and their manifestation in mechanical devices) have performed poorly and hence never left university labs around the world. Recently, however, fast hardware and massive amount of data have allowed revisiting one particular AI algorithm invented in the 80s, namely Artificial Neural Networks (ANN), and increasing the size of the networks used in these models. This was exemplified via image processing for recognizing hand-written digits and resulted in amazing results. Inspired by this success ANN (now known as Deep Learning (DL)) was quickly picked up by other research fields where similar successes have been witnessed.

DL algorithms can now outperform humans on a number of tasks. Moreover, they can, to a certain degree, learn new tasks. An important point in this regard is that the algorithm is so complex that it is next to impossible to understand its inner workings. So, we seem to be facing a reality where AI, in a not too distant future, will be used to make decisions (simply because it is of better than humans). This raises a number of ethical and regulative questions such as, for instance, 1) how we ensure that AI systems are not discriminating against certain groups in the population, 2) how do we ensure transparency about the decisions made by AI systems, and relatedly 3) could and should individuals be given a substantial right to an explanation of decisions made by such systems and a substantial right not to be subjected to automated decision-making (GDPR). Since many of the currently developed AI systems operate on the basis of large amounts of data, the development and use of such systems also reinvigorate the ethical issues related to ‘Big data’. Finally, there are problems related to the efficacy and safety of AI systems. This raises questions not only of how appropriate monitoring of the development of these systems can be secured, but also and more importantly about the appropriate domains for use.

These questions and related questions are the core focus of the PhD course on ‘AI for the people’. The aim is to raise an awareness in the participants. To this end the course will be a combination of lectures, debates and an assignment, and includes the following topics:

• Introduction to AI
• Ethical issues in the development and use of AI
• Industry perspective on AI

Organizers: Professor Thomas B. Moeslund, tbm@create.aau.dk

Lecturers:  Thomas B. Moeslund, Thomas Ploug and Bjørn Skou Eilertsen

ECTS: 2

Time: September 7  &  Oktober 1 2020, from 9:00-16:00

Place:

City: 9000, Aalborg

Number of seats: 30

Deadline: 17 August 2020

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to AI for the People 

Description: The notion of Artificial Intelligence (AI) dates back approx. 70 years as a research field and even longer if one considers fiction writers. A number of different definitions of AI has been suggested over the years, but none seem to capture what AI is. This might be due to the fact that AI is about computer algorithms that behave intelligently. And since the capabilities of computer algorithms improve over time, no static definition is possible.

One aspect of AI is the ability to learn or adapt dynamically. This concept has inspired numerous Sci-fi books and movies with the underlying theme of man vs AI (often manifested in a robot). From this follows naturally ethical and regulatory considerations. But until recently, such considerations (see for example the three Robotic laws defined by the sci-fi writer I. Asimov) have been speculative since current AI algorithms (and their manifestation in mechanical devices) have performed poorly and hence never left university labs around the world. Recently, however, fast hardware and massive amount of data have allowed revisiting one particular AI algorithm invented in the 80s, namely Artificial Neural Networks (ANN), and increasing the size of the networks used in these models. This was exemplified via image processing for recognizing hand-written digits and resulted in amazing results. Inspired by this success ANN (now known as Deep Learning (DL)) was quickly picked up by other research fields where similar successes have been witnessed.

DL algorithms can now outperform humans on a number of tasks. Moreover, they can, to a certain degree, learn new tasks. An important point in this regard is that the algorithm is so complex that it is next to impossible to understand its inner workings. So, we seem to be facing a reality where AI, in a not too distant future, will be used to make decisions (simply because it is of better than humans). This raises a number of ethical and regulative questions such as, for instance, 1) how we ensure that AI systems are not discriminating against certain groups in the population, 2) how do we ensure transparency about the decisions made by AI systems, and relatedly 3) could and should individuals be given a substantial right to an explanation of decisions made by such systems and a substantial right not to be subjected to automated decision-making (GDPR). Since many of the currently developed AI systems operate on the basis of large amounts of data, the development and use of such systems also reinvigorate the ethical issues related to ‘Big data’. Finally, there are problems related to the efficacy and safety of AI systems. This raises questions not only of how appropriate monitoring of the development of these systems can be secured, but also and more importantly about the appropriate domains for use.

These questions and related questions are the core focus of the PhD course on ‘AI for the people’. The aim is to raise an awareness in the participants. To this end the course will be a combination of lectures, debates and an assignment, and includes the following topics:

• Introduction to AI
• Ethical issues in the development and use of AI
• Industry perspective on AI

Welcome to AI for the People 

Description: The notion of Artificial Intelligence (AI) dates back approx. 70 years as a research field and even longer if one considers fiction writers. A number of different definitions of AI has been suggested over the years, but none seem to capture what AI is. This might be due to the fact that AI is about computer algorithms that behave intelligently. And since the capabilities of computer algorithms improve over time, no static definition is possible.

One aspect of AI is the ability to learn or adapt dynamically. This concept has inspired numerous Sci-fi books and movies with the underlying theme of man vs AI (often manifested in a robot). From this follows naturally ethical and regulatory considerations. But until recently, such considerations (see for example the three Robotic laws defined by the sci-fi writer I. Asimov) have been speculative since current AI algorithms (and their manifestation in mechanical devices) have performed poorly and hence never left university labs around the world. Recently, however, fast hardware and massive amount of data have allowed revisiting one particular AI algorithm invented in the 80s, namely Artificial Neural Networks (ANN), and increasing the size of the networks used in these models. This was exemplified via image processing for recognizing hand-written digits and resulted in amazing results. Inspired by this success ANN (now known as Deep Learning (DL)) was quickly picked up by other research fields where similar successes have been witnessed.

DL algorithms can now outperform humans on a number of tasks. Moreover, they can, to a certain degree, learn new tasks. An important point in this regard is that the algorithm is so complex that it is next to impossible to understand its inner workings. So, we seem to be facing a reality where AI, in a not too distant future, will be used to make decisions (simply because it is of better than humans). This raises a number of ethical and regulative questions such as, for instance, 1) how we ensure that AI systems are not discriminating against certain groups in the population, 2) how do we ensure transparency about the decisions made by AI systems, and relatedly 3) could and should individuals be given a substantial right to an explanation of decisions made by such systems and a substantial right not to be subjected to automated decision-making (GDPR). Since many of the currently developed AI systems operate on the basis of large amounts of data, the development and use of such systems also reinvigorate the ethical issues related to ‘Big data’. Finally, there are problems related to the efficacy and safety of AI systems. This raises questions not only of how appropriate monitoring of the development of these systems can be secured, but also and more importantly about the appropriate domains for use.

These questions and related questions are the core focus of the PhD course on ‘AI for the people’. The aim is to raise an awareness in the participants. To this end the course will be a combination of lectures, debates and an assignment, and includes the following topics:

• Introduction to AI
• Ethical issues in the development and use of AI
• Industry perspective on AI

Organizers: Professor Thomas B. Moeslund, tbm@create.aau.dk 

Lecturers: Professor Thomas B. Moeslund, tbm@create.aau.dk 

ECTS: 2.0

Time: 09, 10 and 24 October 2024

9 October: 09:00-16:00
10 October: 10:00-16:00
24 October: TBA


Place: Aalborg University

09 and 10 October 2024: Fibigerstræde 14 room 58
24 October Rendsburggade 14 room 1/1.229

Zip code: 9220

City: Aalborg

Number of seats: 30

Deadline: 18 September 2024


Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

For external PhD students: This course is a general course and is prioritized for PhD Students enrolled at Aalborg University. If there are available seats, PhD students from other universities will be accepted. You will be notified shortly after the deadline if you have been accepted.

For inquiries regarding registration, cancellation or waiting list, please contact the PhD administration, aauphd@adm.aau.dk

Welcome to Algorithmic Design of Nonlinear Control

Description: This course will challenge your believe that only linear control systems can be algorithmically designed. We will show that nonlinear systems can be treated with modern software tools for nonlinear control.

Linear matrix inequalities are used as a standard tool for linear system design. For many years, nonlinear systems did not have any counterpart. However, recently the control society identified sums of squares as a good tool for the analysis and synthesis of nonlinear control systems. The majority of questions in control reduce to checking the positivity of a function. In this course we will address polynomial functions, and present algorithms for computing nonlinear controls via certificates of positivity. The course will bring you on a journey from Hilbert's 17th problem over Positivestellensatz to Schmüdgen's Positivstellensatz and its simplifications implemented in e.g. SOSTOOLS.

During exercise sessions the students will be introduced to toolboxes in MATLAB e.g. SOSTOOLS for solving various nonlinear control problems.

Organizer: Professor Rafael Wisniewski, Automation & Control AAU

Lecturers: Assistant Professor Christoffer Sloth, Automation & Control AAU
and Professor Rafael Wisniewski, Automation & Control, AAU

ECTS: 3

Time:

20-21 November, 2014 and

26-28 November, 2014

Place: Aalborg University

Zip code: 9220

City: Aalborg

Number of seats: 50

Deadline: 1 November, 2014

Welcome to Analysis and Gradient Based Optimization of Laminated Composite Structures

Description

Background and Motivation: Polymeric resin fibre reinforced materials (FRP´s or composite materials) are being used increasingly for structural applications where properties such as high strength, high stiffness and low weight are determining design parameters. The driving force behind the development and application of these materials has been the demands posed by the aerospace industry, but the use of advanced composite materials is expanding rapidly to other industrial sectors as well. Pertinent examples of this include applications for ship structures, automotive and train applications, wind turbine blades and civil engineering applications including bridge structures.

Objectives and Contents: The purpose of the course is to present the participants with a general overview and an introduction to recent advances and modern techniques for analysis and gradient based design optimization of advanced laminated composite structures. The following topics will be treated:

• Laminae and laminates: fiber and resin materials, modelling of the laminae, classical lamination theory (CLT), shear-deformation plate theories
• Fracture and failure of composite materials - focus on failure criteria and their use
• Finite element analysis of laminated composite structures with focus on shell and solid shell formulations
• Introduction to basic concepts of gradient based structural optimization
• Parameterization choices for laminated composites (continuous fiber angles and thicknesses, lamination parameters, Discrete Material Optimization (DMO), Discrete Material and Thickness Optimization (DMTO), etc.)
• Efficient methods of Design Sensitivity Analysis for gradient based structural optimization
• Inclusion of manufacturing constraints
• Gradient based design optimization of laminated composite structures for linear and nonlinear problems including buckling problems

Course Language: The course will be given in English.

Teaching Material: Lecture notes will be made available for registered course attendees.

Furthermore, a Matlab skeleton script for analysis and design optimization of laminated composite plates using isoparametric finite elements is provided as basis for part of the assignments.

Course Format and Work Load: The course will consist of a condensed session comprised of 5 full days of lectures, work on assignments, and discussions at AAU. After the course session the course participants (PhD students) are expected to solve and submit homework assignments. Diplomas will be issued on the basis of course participation and evaluation of homework assignments, and entitle Ph.D. students to 5 ECTS, corresponding to 140 hours of work load.

Participants: Participants are expected to have a basic knowledge in mechanics of solids corresponding to undergraduate level (mechanical, aero, civil and ship/maritime engineering). The course is aimed specifically at Ph.D. students, but the course is also recommended for industrial engineers and engineering scientists. University staff and final year M.Sc. students are welcome as well. University staff, M.Sc. students and participants from industry may be exempted from the homework assignments and the course evaluation/examination. Course assignments are based on Matlab scripts, and it is expected that participants have Matlab installed. The public domain code Octave can also be used (https://www.gnu.org/software/octave/index.html).

Earlier Events: The course has been held biannually since 2004 to 2014 as “Analysis and Design Optimisation of Laminated Composite Structures”. However, since 2016 the course has been revised such that more focus is put on gradient based methods for the design optimization part, and the course assignments have thereby also been changed significantly.

Course participation is free for national Ph.D. students and university staff. Participants from industry will be charged DKK 12,500 (DKK 2,500 pr. ECTS). International Ph.D. students and university staff get a discount of 90% and will be charged DKK 1,250.
If you are from outside Aalborg University and you wish to enroll in one of our PhD courses, you must create a profile. This is done by clicking on “create new account” and filling out the form. 
For further information please contact Professor Erik Lund, Phone (+45) 9940 9312, E-mail: el@mp.aau.dk

Organizer: Department of Materials and Production, Aalborg University (www.mp.aau.dk)  Aalborg University, The Doctoral School of Engineering and Science, (www.phd.teknat.aau.dk)
Professor Erik Lund, e-mail: el@mp.aau.dk In collaboration with DCAMM, Danish Center for Applied Mathematics and Mechanics (www.dcamm.dk).

Lecturers: Erik Lund, Johnny Jakobsen and Esben Lindgaard, Department of Materials and Production, Aalborg University

ECTS: 5

Time: 14-18 May 2018

Place: Department of Materials and Production, Aalborg University, Fibigerstræde 16

Zip code: 9220

City: Aalborg Øst

Number of seats: 30

Dealine: 27 April 2018

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Application of Phasor Measurement Units for monitoring of power system And RTDS Technology

Description:

Under the supervision of the smart grid, online visualization of the power system states is
highly demanded, due to the growing complexity of the operation of the power system networks. With the
advent of the phasor measurement units (PMUs), which are much faster as compared to RTUs, the PMU
measurements can be best utilized for the online visualization of the power system states. Additionally, with
the introduction of real-time simulation tools, such as the Real Time Digital Simulator (RTDS), real-time test
and validation of the power system state estimation is achievable. Such simulations will provide the required
confidence in the design of the state estimation and also validate its performance in a real-time environment.
This four-day course provides an overview and hands-on experience into the use of phasor measurement units in novel transmission power system network:

• Motivation for Synchronized Measurements
• Synchrophasor Fundamentals: PMU Measurements
• Synchrophasor Fundamentals: Estimation
• Synchrophasor Fundamentals: Setting PMU
• Synchrophasor Fundamentals: Data Quality
• Synchrophasor Fundamentals: Standards
• PMU Applications
• PMU-Based State estimation
• PMU for Novel State estimations

The course will also focus on the applicability and practical implementation of the models, and cover the following main topics:

• Overview of the principles of operation of the RTDS Simulator and an introduction to the electromagnetic transients algorithm used.
• Introduction to the RSCAD software suite and its modules.
• Build and run a number of power system simulation cases showing the capabilities and limitations of the RTDS Simulator.
• Use of various I/O cards – GTAO, GTAI, GTDO, GTDI and GTFPI.
• Introduction to developing an interface between an external protective relay and the RTDS Simulator for closed-loop testing.
• Use RSCAD’s CBuilder module to create user defined component models.
• Use scripts to automate the process of running simulation cases.
• Use of RTDS’ GTNET hardware for GOOSE, Sampled Values and MMS Server applications;
• Use of RTDS’ MMS Voyageur software for MMS Client applications;
• Use of RTDS’ Protection and Automation Suite (MMS Server Simulator) software for MMS Server applications;

Prerequisites: Degree in Electrical Power System or similar
Matlab/Simulink knowledge is recommended for the exercises.

Form of evaluation: Exercises during course. participate in 4 days course. At the end, participants have to do project works based on materials of the course. There are 4 groups (each group consists of 5 persons).

Group1: installing PMU based SE for IEEE 14 Bus
Group2: Dynamic state estimation for Voltage and Current of IEEE 9 Bus
Group3: Data Quality for IEEE 9 Bus system
Group4: Simulink to RSCAD (IEEE 9 Bus)

Organizer: Associate Professor Filipe Faria da Silva, email: ffs@et.aau.dk, Aalborg

Lecturers: Associate Professor Filipe Faria da Silva, email: ffs@et.aau.dk, Aalborg, Postdoc Hesam Khazraj, email: hkh@et.aau.dk, Aalborg

ECTS: 3

Time: November 12-14, 2018

Place: 

City: 

Number of seats: 20

Deadline: October 22 2018

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description:
Artificial Intelligence/Machine Learning is becoming an increasingly important tool for mechanical and manufacturing engineers, whether you work with materials, processes or mechanical / manufacturing systems.
This course will give an introduction to emerging tools in AI/ML such as broad range of deep learning techniques that are highly relevant for the modern mechanical / manufacturing engineer. In the course valuable methods and specific industrial applications are addressed. Topics will include:

• Machine learning fundamentals

• Deep learning concepts within computer vision, natural language processing, and intelligent agents

• Deep learning methods including convolutional neural (CNN) networks, recurrent neural networks (RNN), auto-encoders, LSTM, and Reinforcement Learning (RL) techniques and algorithms

• Selected industrial applications if AI/ML such as defect detection in materials and surfaces, quality inspection, predictive analytics, human-machine interaction with virtual assistants, self-learning robots and automatic optimisation of machine parameters

• Software, frameworks, tools and public datasets

Application implementations will be tested in the AAU Smart Lab at the Department for Materials and Production

Organizers: Associate Professor, Simon Bøgh, sb@mp.aau.dk  

Lecturers: Associate Dimitris Chrysostomou, AAU, Assistant Professor Chen Li, AAU, Associate Professor Nestor Arana Arexolaleiba, Mondragon University, Spain (Visiting Professor AAU)

ECTS: 5.0

Time: August 2022

Place: Aalborg University

Number of seats:

Deadline: 3 weeks prior to course start

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Applied Clinical Omics technologies for Personalized medicine

Description:

Omics technologies including genomics, transcriptomics, proteomics and metabolomics are now key technologies in multiple fields of research and a highly active domain in health and medical investigation. Omics is an interdisciplinary research field that coalesces researchers from many different areas of biomedical research into one of the most likely disciplines to successfully foster the translation of basic scientific knowledge into clinical applications for the benefit of patients. For instance, proteomics and applied mass spectrometry are vital tools to investigate the human proteome in a clinical perspective (www.hupo.org).

This PhD course will focus on advanced theoretical and practical aspects of Omics strategies in life sciences as well as medical research. Our focus will address the application of omics strategies to address a diverse range of medical pathologies, including but not limited to autoimmune disorders, diseases associated to neuro-inflammation and neurodegeneration as well as chronic pain conditions. Omics are currently utilized extensively to identify biomarker patterns for detection of disease risk, patient’s stratification, identification of responders to a particular treatment, or elucidation of mechanism of disease or drug action with the ultimate goal of patient safety and better health outcome.

The course will be a combination of lectures and laboratory demonstrations with a hands-on experimental part. Considering the value and importance of omics, and a rapidly growing trend, this course aims at providing front edge information about current advanced methodologies applied in medical omics through real-life examples. Hence, participants will be able to translate the presented strategies and methods into their own health and medical related research.

Lectures:

• Theoretical and strategic introduction to omics technologies in the scope of clinical research.
• Strategies for clinical proteomics, genomics and metabolomics for personalized medicine in several fields including autoimmune disorders, neurodegenerative diseases and chronic pain.
• Project design for omics type projects
• Sample handling from patients (biobank), animal models, or in-vitro systems to the mass spectrometer and beyond
• Principles of mass spectrometry and sample preparation for MS
• Applications for quantitative proteomics and metabolomics in health and medical science.

Literature
Notes, literature and exercise instruction will be distributed at the course

Prerequisites
None

Evaluation

Active participation in the theoretical and experimental course

Organizer: Associate professor Allan Stensballe, email: as@hst.aau.dk

Lecturers: Associate Professor Allan Stensballe, Assistant Professor Parisa Gazerani, Assistant Professor Tue Bjerg Bennike, Aalborg University,Staff Scientist Michael Kruse Meyer and invited lectures

ECTS: 2.5

Time: 19, 20 and 21 June 2019 (19.6 and 20.6: 8.15 - 16.15; 21.6: 8.15 - 12.00)

Place: Aalborg University, Fredrik Bajers Vej 7E, room E3-209  

Zip code: Aalborg Øst

City: 9220

Number of seats:

Deadline: 29 May 2019 

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description:
Artificial intelligence (AI) has significantly revolutionized research activities and industrial applications in image processing and natural language processing. Likewise, the synergy of power electronics and computer science is expected to unleash great potentials in power electronic systems as well with their transition towards data-rich ones. From the power electronics perspective, this course aims to focus on two essential aspects of this interdisciplinary field, i.e., artificial intelligence and advanced data analytics. It is organized following a typical pipeline when implementing data-driven solutions in power electronics, ranging from the initial data collection to the final decision-making. As a 3-day course, it includes fundamentals, tools, applications, outlook, and hands-on exercises, which are specifically tailored for power electronic applications. Combining with several case studies where AI has shown great benefits, the attendees are expected to establish solid foundations and skills of AI and data analytics to address core challenges in data-driven applications in power electronics. 

Day 1: Fundamentals of data-driven solutions in power electronics (Shuai Zhao, Huai Wang, 8:30-16:30) 
This course will first get the attendees familiar with the background and existing development of data-driven research in the power electronic field. It will then establish the basics of two relevant aspects of data-driven solutions, i.e., AI tools and advanced data analytics. It will cover the following topics: 

·     Data-driven solutions in power electronics 

·     Artificial intelligence tools in power electronics  

·     Neural network for power electronic applications 

·     Advanced data analytics in power electronics 

Day 2: Case studies and application examples in power electronics (Shuai Zhao, Huai Wang, 8:30-16:30) 
With the fundamental knowledge of data-driven solutions in power electronics, several case studies and promising applications, where AI and data analytics have illustrated a great superiority compared to conventional methods, will be detailed. It will cover the following topics: 

·     Prognostics and health management (PHM) in power electronics 

·     Case study I: AI-assisted experiment design and potentials in power electronics 

·     Case study II: Non-invasive condition monitoring of power converter 

·     Case study III: Information fusion for remaining useful life prediction in power electronics 

Day 3: Frontiers of data-driven methods and team project (Shuai Zhao, 8:30-16:30) 
To have a further overview of this rapidly dynamic field, the development trend, cutting-edge tools, and further promising directions of this synergy field will be outlooked. Moreover, a hands-on team project will be introduced and instructed. It will cover the following topics: 

·     Frontiers of data-driven research in power electronics and beyond 

·     Team Project discussion support (based on a Nature Energy paper) 

Prerequisites: 

·     Fundamentals of power electronics 

·     Fundamentals of probabilistic models and statistical analysis 

·     Experience with MATLAB/Python 

Form of evaluation: 
The course is accompanied by a hands-on team project so that the theoretical tools introduced in the course can be implemented in real applications. The project is mainly formulated following the paper ”Data-driven prediction of battery cycle life before capacity degradation”, which is published in Nature Energy in 2019. The course evaluation will be based on this team project report. 

Organizer:
Professor Huai Wang, hwa@energy.aau.dk 
Postdoc, Shuai Zhao szh@energy.aau.dk 

Lecturers:
Huai Wang, Aalborg University 
Shuai Zhao, Aalborg University 

ECTS: 3

Time: 6-8 April 2022

Place: AAU Energy, Aalborg 

Number of seats: 25

Price: 6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT

Deadline: 16 March 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Biophysical Expression, Affect & Movement (BEAM)

Organizer: Dan Overholt

Lecturers: Dan Overholt (US/DK), Elizabeth Jochum (US/DK), Mark-David Hosale (US/CA),  Alan Macy (US), Grisha Coleman (US), and Marco Donnarumma (DE/IT).

ECTS: 3

Date/Time: 27, 28, 29 May 2024

Deadline: 06 May 2024

Max no. of participants: 20

Description: Biophysical Expression, Affect & Movement (BEAM) introduces students to cutting edge research trends and technology platforms that monitor and augment human performance across both the creative industries and health sectors.  The course offers hands-on workshop activities using advanced sensor technologies for physiological data, applied to real-time performance and augmented human capabilities with computation, including machine learning.

One platform to be explored is The Source by BioMECI with guest lecturers / developers Mark-David Hosale and Alan Macy. Design and integration with other platforms will also be explored, for example Bio-X sensors integrating machine-learning approaches to multimodal human-computer interaction. The course includes invited lectures & workshops with Grisha Coleman (Northeastern University, US) and Marco Donnarumma (IT/DE) addressing important topics on critical computing, AI, and ethics as they relate to movement motion capture data, prosthetics, and research. The course will have a strong focus on somatic practices (f.ex. Feldenkreis), and practical work on embodied interaction. This course has cross-over appeal for creative computing applications (audiovisual interaction, sound and music computing) and health/rehabilitation applications (tele-health, digital health solutions/monitoring). Programming experience, Design of HCI systems, interest in affective computing and real-time systems exploring the arts, such as music / dance & movement / visual forms of expression and/or interest in working with medical devices/sensing/health monitoring devices for training and rehabilitation.

The course will be hosted by the Sound & Music Computing research group and take place in both the Augmented Performance Lab  and the  Manufakturet labs. The course will be supported by researchers from the RELATE Research Laboratory for Art and Technology.

Prerequisites: Programming experience, Design of HCI systems, and/or Interest in affective computing and real-time systems exploring the arts, such as music / dance & movement / visual forms of expression and/or interest in working with medical devices/sensing/health monitoring devices for training and rehabilitation.

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Required Reading

• Donnarumma, M. (2017). On Biophysical Music. In: Miranda, E. (eds) Guide to Unconventional Computing for Music. Springer, Cham. https://doi.org/10.1007/978-3-319-49881-2_3 (pdf)
  
• Tanaka, A. (2019). Embodied Musical Interaction. In: Holland, S., Mudd, T., Wilkie-McKenna, K., McPherson, A., Wanderley, M. (eds) New Directions in Music and Human-Computer Interaction. Springer Series on Cultural Computing. Springer, Cham. https://doi.org/10.1007/978-3-319-92069-6_9 (pdf)
  

Mark-David Hosale is a computational artist and composer. He is an Associate Professor and Chair of Computational Arts in the School of the Arts, Media, Performance, and Design, at York University, Toronto, Ontario, Canada. He has given lectures and taught internationally at institutions in Denmark, The Netherlands, Norway, Canada, and the United States.  His work explores the boundaries between the virtual and the physical world. His practice is varied, spanning from performance (music and theatre) to public and gallery-based art. His interdisciplinary practice is often built on collaborations with architects, scientists, and other artists.

Grisha Coleman is a time-based artist working in areas of choreography and performance, experiential technology, and sound composition. Her practice and research explore relationships across physiological, technological, and ecological systems; human movement, our machines, and the places we inhabit. Her echo::system project is a springboard for re-imagining the environment and environmental justice through participatory installation, chorography and composition in live performance, media and computation. Her current project, The Movement Undercommons: Technology as Resistance | Future Archives, creates a repository of vernacular movement data, imagining a lexicon centered around identity and embodied cultural narrative. Her work has been generously supported through a Radcliffe Fellowship(21/22), The National Endowment for the Arts in Media grants, the Rockefeller Multi-Arts Project [MAP] Fund, Creative Capital, the Jerome Foundation, the Surdna Foundation Thriving Cultures Grant, the MacDowell Arts Colony, the New York Foundation for the Arts, Carnegie Mellon University’s STUDIO for Creative Inquiry, Pioneer Works, the Rockefeller Foundation Bellagio Center, and Stanford University’s Mohr Visiting Artist Fellowship.She holds the position of Professor of Movement, Computation, and Digital Media in the in the College of Arts, Media, and Design at Northeastern University, and an affiliation with the School of Arts, Media, and Engineering, the School for the Future of Innovation in Society, and the Center for Race and Democracy at Arizona State University. Ms. Coleman is a New York City native.

Marco Donnarumma (DE) is an artist, performer, stage director and theorist weaving together contemporary performance, new media art and interactive computer music since the early 2000s. He manipulates bodies, creates choreographies, engineers machines and composes sounds, thus combining disciplines, media and technology into an oneiric, sensual, uncompromising aesthetics. He is internationally acknowledged for solo performances, stage productions and installations that defy genres, and where the body becomes a morphing language to speak critically of ritual, power and technology. The 7 Configurations cycle, his latest project, includes dancetheater productions, performances and robotic installations. By experimenting with the corporeal and psychological relationships of four human performers and six AI prostheses, the pieces attempt to dissect the conflicts between AI and body politics. In 2019, he co-founded the performance group Fronte Vacuowith Margherita Pevere and Andrea Familari. Their ongoing saga, Humane Methods, consists of hybrid live art events as social experiments, where human performers and audiences, non-human organisms and AI-driven machines expose the violence of today’s algorithmic societies. During the seasons 2022-24, they are artists in residence at Volkstheater Wien.

Dan Overholt is an Associate Professor at Aalborg University Copenhagen. His research interests include advanced technologies for interactive interfaces and novel audio signal processing algorithms, with a focus on new techniques for creating music and interactive sound. He is involved in the development of tangible interfaces and control strategies for processing human gestural inputs that allow interaction with a variety of audiovisual systems. Dan is also a composer, improviser, inventor and instrument builder who performs internationally with his new musical instruments and custom sound synthesis and processing algorithms. Dr. Overholt received a PhD in Media Arts and Technology from the University of California, Santa Barbara, and a M.S. in Media Arts and Sciences from the Massachusetts Institute of Technology. He has about 90+ peer reviewed publications and two patents (one provisional).

the RELATE Research Laboratory for Art and Technology at Aalborg University. Her research uses the visual and performing arts as catalysts for re-thinking how we design and implement robots and other assistive technologies. From industrial robots to exoskeletons, Dr. Jochum’s work involves transdisciplinary collaboration in human-robot interaction, health, and engineering to develop creative, value-sensitive, and human-centered approaches to ensure the technologies we build address the real needs of people. She coordinated the European ABRA project on Artificial Biology, Robotics and Art, and the ImprovAIze project on machine learning, dance improvisation, and wearables for artistic practice and rehabilitation. She served on the steering committing of Aalborg University Robotics, the Arts, Health, and Humanities center at AAU. She was named one of the top 50 Women in Robotics by Robohub in 2021. 

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

CANCELLED

Welcome to Advanced Program Verification

Description:

Learning objectives: 

Organizer: Associate Professor Rene Rydhof Hansen

Lecturers: Flemming Nielson (DTU), Aslan Askarov (AU)

ECTS: 2

Time: October-November 2020

Place: 

Zip code: 

City: 

Number of seats: 25

Deadline: 

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Artificial Intelligence in Electrical Energy Systems


Description: Artificial intelligence (AI) has recently become ubiquitous in our society, with applications in search, image understanding, apps, mapping, medicine, drones, and self-driving cars. Core to many of these applications are visual recognition tasks such as image classification, localization and detection. On the other hand, AI has also been used in Electrical Engineering for many decades for data-driven modelling of system whose analytic modelling was hard or simply not possible to do. For instance, they have been widely used for load/generation/price forecasting, for modelling nonlinear parts of the industrial control systems and for creating surrogate models of complex systems. All these applications are enabled by the artificial neural networks – the fundamental workhorses of the AI.

However, as opposed to past decades when neural networks were small and comprised only a few neurons, recent dawn of the big data age (characterized by the unprecedented access to large computational resources and big datasets) has enabled the creation of much larger networks. They have greatly advanced the computer vision field but have recently also enabled many new applications in the electrical engineering field.
In a nutshell, this course is focused on providing the attendees the following material: a) AI historical background in electrical engineering and wider, b) an understanding and fundamental characteristics of artificial neural networks, and c) practical applications of AI proposed by the lecturers that have solved some of the long standing research problems in electrical engineering. All models will be provided to attendees and experimental lab demonstration is expected as well.
Upon completing the course, the participants will gain insight how to obtain a high accuracy surrogate model of a power electronics systems, utilize the surrogate for multi-objective optimization problems or synthesis of complex power electronics controllers.

Day 1: General information about AI, Tomislav Dragičević (4.5 hours) + Mateja Novak (2.5 hours)
9:00 – 10:00 Artificial intelligence – how is it revolutionizing the world
10:00 – 10:30 Features of neural networks – the workhorses of AI
10:30 – 11:00 Coffee break
11:00 – 12:00 Artificial intelligence in electrical engineering – historical background
12:00 – 13:00 Lunch break
13:00 – 14:00 Application of AI to optimize design of power electronic systems
14:00 – 15:00 Imitation learning of computationally heavy controllers
15:00 – 15:30 Coffee break
15:30 – 16:30 AI for optimizing the control parameters of industrial control systems

Day 2: AI laboratory exercises. Tomislav Dragičević (3.5 hours) + Mateja Novak (3.5 hours)
08:30 – 10:30 Laboratory 1: AI-aided design for reliability of power electronics systems
10:30 – 11:00 Coffee break
11:00 – 12:00 Laboratory 2: AI-aided imitation learning of industrial control systems (part 1)
12:00 – 13:00 Lunch break
13:00 – 14:00 Laboratory 2: AI-aided imitation learning of industrial control systems (part 2)
14:00 – 15:00 Laboratory 3: AI-aided tuning of control parameters (part 1)
15:00 – 15:30 Coffee break
15:30 – 16:30 Laboratory 3: AI-aided tuning of control parameters (part 2)

Prerequisites:
General knowledge about electrical engineering field.
Practicing knowledge in power electronic systems.
Experience in using Matlab/Simulink (Deep Learning toolbox, Parallel Computing toolbox)
The course is recommended for PhD students and power electronic control engineers focusing on multi-objective optimization problems and implementation of complex control algorithms

Form of evaluation: Report evaluated by the lecturers.

Key References:
 T. Dragičević, P. Wheeler and F. Blaabjerg, "Artificial Intelligence Aided Automated Design for Reliability of Power Electronic Systems," in IEEE Transactions on Power Electronics, vol. 34, no. 8, pp. 7161-7171, Aug. 2019.
 T. Dragičević and M. Novak, "Weighting Factor Design in Model Predictive Control of Power Electronic Converters: An Artificial Neural Network Approach," in IEEE Transactions on Industrial Electronics, vol. 66, no. 11, pp. 8870-8880, Nov. 2019.
 M. Novak, T. Dragicevic and F. Blaabjerg, "Weighting factor design based on Artificial Neural Network for Finite Set MPC operated 3L-NPC converter," 2019 IEEE Applied Power Electronics Conference and Exposition (APEC), Anaheim, CA, USA, 2019, pp. 77-82.
 S. Mohamed, S. Rovetta, T. D. Do, T. Dragičević and A. A. Z. Diab, "A Neural-Network-Based Model Predictive Control of Three-Phase Inverter With an Output LC Filter," in IEEE Access, vol. 7, pp. 124737-124749, 2019.

Organizer: Prof. Tomislav Dragičević (tdr@et.aau.dk)

Lecturers: Prof. Tomislav Dragičević, dr. Mateja Novak

ECTS: 2

Time: 24 – 25 September 2020

Place: 

Zip code: 

City: 

Number of seats: 30

Deadline: 3 September 2020

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Welcome to Cyber Security for Microgrids


Description:

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. All these facts 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: (a) identifying the vulnerable access points in microgrid controllers, (b) introduce the most prominent cyber-attacks, (c) detection of cyber-attacks in in real-time, (d) removal of these attack elements and ensuring stability/preventing system shutdown, (e) design of resilient controllers for microgrids, which heals by itself despite any cyber intrusion attempts. All models will be provided to attendees and experimental lab demonstration is expected as well along with discussion on future research ideas.

Day 1: General information about cyber security and its impact in microgrids – Tomislav Dragičević (2.5 hours) + Subham Sahoo (2.5 hours)
9:00 – 10:00 Microgrids – Role in modern power systems
10:00 – 10:30 Basic control and operation philosophies of microgrids
10:30 – 11:00 Coffee break
11:00 – 12:00 Cyber security in power systems – Lookback into the past events
12:00 – 13:00 Lunch break
13:00 – 14:00 Vulnerability assessment of microgrids to different kinds of attacks
14:00 – 15:00 Design of cyber-attack detection and mitigation strategies for microgrids
15:00 – 15:30 Coffee break
15:30 – 16:30 Design of resilient self-healing controllers for microgrids

Day 2: Cyber security laboratory exercises. Tomislav Dragičević (1 hour) + Subham Sahoo (4 hours)
09:30 – 10:30 Laboratory 1.1: Detection of cyber attacks in microgrids (part 1)
10:30 – 11:00 Coffee break
11:00 – 12:00 Laboratory 1.2: Detection of cyber attacks in microgrids (part 2)
12:00 – 13:00 Lunch break
13:00 – 15:00 Laboratory 2: Design of resilient controllers for microgrids
15:00 – 15:30 Coffee break
15:30 – 16:30 Laboratory 3: Mitigation of cyber attacks in microgrids

Prerequisites:
General knowledge about electrical engineering field.
Practicing knowledge in power electronic systems and control theory.
Experience in using Matlab/Simulink

Form of evaluation: Report evaluated by the lecturers.

Organizer: Prof. Tomislav Dragičević

Lecturers: Prof. Tomislav Dragičević; Dr. Subham Sahoo

ECTS: 2

Time: 25 – 26 May 2020

Place: 

Zip code: 

City: 

Number of seats: 30

Deadline: 5 May 2020

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Description:
Building occupants are the end-users of the energy used in buildings. ICT based solutions in buildings can contribute to saving energy and can support the maintenance and operation of buildings. Therefore it can be expected that automated solutions in all energy related processes in buildings will become more prevalent in the future. The application of ICT solutions in buildings requires interdisciplinary knowledge and competences in order to find and design integrated solutions that can be operated in a sustainable way: supporting the occupants needs, dimish environmental impacts from buildings and ease operation and maintenance. Human centred design of ICT/smart solutions requires knowledge about human perception and human building interaction and human-centred design in architecture today requires knowledge on ICT/smart solutions for buildings and their potential. The course brings together students from different study fields and offers them opportunity to broaden their insight in interaction between humans and the built environment. The lecturers are based on latest research and have multi-disciplinary background and address this interdisciplinarity in the lectures on: ICT/big data/automation solutions in buildings: functions, objectives; occupant behaviour in real buildings - outcome from field studies; Experience with ICT solutions from field studies; framework/models for human building interaction; personal control perception in buildings and future approaches for occupant-centric design. In addition to the lectures, the course builds on reading and observation tasks, and comprises interactive workshops and provides sufficient room for discussion and reflection on the course topic in relation to the diverse PhD topics. The course will be offered online.

Organizer: Professor Runa T. Hellwig

Lecturers:
Lecturers from different fields: ICT/big data/automation solutions in buildings: functions, objectives; occupant behaviour in real buildings - outcome from field studies; Experience with ICT solutions from field studies; framework/models for human building interaction; personal control perception in buildings; future approaches for occupant-centric design; interactive workshop based on PhD topics

ECTS: 3.0

Time: 19. 20 and 21 December 2022

Place: Online or hybrid

Number of seats: 15

Deadline: 28 November 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Organizer:     Professor Birgitte Bak-Jensen, bbj@energy.aau.dk

Lecturers:      Professor Birgitte Bak-Jensen, Aalborg University

Associate Prof. Jayakrishnan Pillai, Aalborg University

Associate Prof. Florin Iov, Aalborg University

Associate Prof. Rasmus Løvenstein Olsen, Department of Electronic Systems, AAU

Assistant Professor Pavani Ponnaganti, Aalborg University

Postdoc, Rakesh Sinha, Aalborg University.

ECTS:               3

Date/Time:   September 26-29, 2023'

Deadline       September 6

Price:               6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT
The Danish universities have entered into an agreement that allows PhD students at a Danish university (except Copenhagen Business School) the opportunity to free of charge take a subject-specific course at another Danish university.

Payment:       A Online link will be annonced after deadline for registration

Place:              AAU Energy, Aalborg

Max no. of participants: 20

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Analytical Methods for Microplastic Quantification in Complex Matrixes

Description: This PhD course addresses the theory of sampling, sample preparation and state-of-the-art analytical techniques to analyze microplastics in environmental matrices.

The course will start with the principles of techniques for sampling of microplastics and with the principles of clean-up of such samples. We will discuss the steps needed in cleaning up samples for natural organic and inorganic matter, as well as getting samples ready for subsequent identification. We will cover approaches and issues for QA/QC of your analysis, here amongst field blanks, laboratory blanks, recovery studies, and what are appropriate sample sizes to obtain statistically robust data.

From here, the focus shifts towards some theory on suitable techniques for microplastics quantification. We will cover the most commonly applied techniques, namely ATR-FTIR and µFTIR imaging – the combination of light microscopy with spectral images generated by Focal Plane Array (FPA) or linear array-based instruments to a particle assembly. The second commonly used spectroscopic method, Raman, is also covered. We address Raman spectroscopy and its application for automated particle selection for faster mapping. The last family of covered techniques are Gas Chromatographic – mass spectrometry based techniques, where we focus on pyrolysis GC-MS as the most commonly used approach. The last step in microplastics research is the interpretation of the obtained data. We provide our solution for it in the software siMPle, which is used for automated µFTIR imaging and Raman imaging data interpretation. You will be taught how it works and will get first-hand experience during our practice session.

All steps of the course require a high degree of expertise and training. This course is aimed to introduce participants to all steps and discuss issues, pros and cons of different approaches, and is in general very open and informally structured to promote discussions. This course requires the participants to read up on the theory before the course, and is evaluated by a subsequent test. All the lectures will be organized and given by experts in the field of microplastic research, and top analysts and product specialists from the most prominent companies involved in analytical instrumentation used in the field.

Lecturers: Claudia Lorenz, Alvise Vianello, Jes Vollertsen

ECTS: 4

Time: October 2023, several lectures over three weeks

Place: online via Zoom

Important information concerning PhD courses:

We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations. 

Description: Low energy harvesting mechanisms are unique opportunities to provide source of electrical energy for autonomous sensors for predictive maintenance applications, self-powered and wireless micro-actuators, monitoring devices for health care, energy hubs, Internet of Things (IoT)-enabled energy networks etc. This PhD course handles the fundamentals of energy harvesting technologies such as thermoelectric, piezoelectric, and electromagnetic devices by introducing recent development techniques and detailed module design. This course will continue with integration principles of the energy harvester modules with the system components to enhance output power performance of the modules. Furthermore, control of electrical output of the devices will be discussed for maximum power point tracking by power electronic converting methods. This course also addresses recent applications of such energy harvesting mechanisms with introducing opportunities, challenges and relevant applications in renewable energy IoT industries.

Day 1:
Morning: Thermoelectric generator model and module design; Alireza Rezaniakolaei (3 hours)
-          The lectures cover history of thermoelectrics, typical thermoelectric systems, basic arrangement & characterizing quantities, challenges for thermoelectrics, contact resistance, effect of geometry and inter-leg heat transfer.

Afternoon: Electromagnetic energy harvesters; Kaiyuan Lu (3 hours)
-          The lectures cover the state-of-the-art designs of electromagnetic energy harvesters, typical design principle, device modelling, characterizing quantities, performance improvement challenges etc.

Day 2:
Morning: Integration of heat exchangers with thermoelectric modules; Alireza Rezaniakolaei (3 hours)
-          The lectures cover coupled thermoelectric device/thermal system design, high performance cooling technologies, cooling energy vs. power generation, integrated model of thermoelectric & heat sinks.

Afternoon: MPPT and power electronic converters; Erik Schaltz (3 hours)
-          The lectures covert thermoelectric generators modelling from power electronics point of view. Fundamentals of Power Electronics, power electronic converters for energy harvester device and maximum power point tracking (MPPT) algorithms for the device will be discussed.

Day 3:
Applications for thermoelectric energy harvesting; Alireza Rezaniakolaei (1:30 hours)
-          The lectures cover integration of the thermoelectric generation with solar power systems and autonomous sensor platforms

Piezoelectric energy harvesting, model, design and applications; Majid Khazaee (2 hours)
-          The lecture does cover basics about piezoelectric materials and material properties.
-          Presenting the different applications of the piezoelectric energy harvesters.
-          Modeling techniques for piezoelectric beams and characteristics of the power output from piezoelectric beams.

IoT applications for low power energy harvesting; Amjad Anvari-Moghaddam (2 hours)
-           The lecture covers a background on IOT definitions and edge devices, energy harvesting technologies and its requirements IoT applications.

Prerequisites: No

Form of evaluation: Completion of design and metaphysics simulation of a form of the energy harvesting mechanisms or power output management of the chosen energy harvesting technology in the selective list of the tasks. The assignment will be done in groups and each group must submit the final report.

Organizer:     Associate Professor, Alireza Rezaniakolaei, alr@energy.aau.dk

Lecturers:      Associate Professor, Alireza Rezaniakolaei (ALR), Aalborg University

Associate Professor, Kaiyuan Lu (KLU), Aalborg University

Associate Professor, Amjad Anvari-Moghaddam (AAM), Aalborg University

Associate Professor, Erik Schaltz (ESC), Aalborg University

Guest researcher, Majid Khazaee (MAD), Aalborg University

ECTS:               2.5

Date/Time:   27-29 November 2023

Deadline:       6 November 2023

Price:               6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT
The Danish universities have entered into an agreement that allows PhD students at a Danish university (except Copenhagen Business School) the opportunity to free of charge take a subject-specific course at another Danish university. Guests at AAU Energy can free attend the course. 

Payment:       A Online link will be annonced after deadline for registration

Place:              AAU Energy, Aalborg

Max no. of participants: 25

Description: Industrial automation and control is posing challenges related to implementation of different control algorithms on real time target hardware. Typically, in the preliminary design process researchers and engineers are using continuous time models and tools from dedicated software platforms such as Matlab/Simulink. Issues related to discretization and implementation of these algorithms on target hardware arises when design is ready. This course aims to provide a walk-through the entire model based design process for typical industrial systems. The course is covering all main stages of the model based design starting from continuous time domain representation and preliminary design of the systems till practical implementation and coding on different real-time target hardware. The course is supported with a large number of theoretical and practical day-to-day implementation exercises. The following topics are covered during the course:
o Typical control structures for industrial systems
o FIR and IIR (LPF, Resonant (BPF, BSF), zero phase shifting) filter design,
o PID and resonant controller design, Auto-tuned Controller design,
o Slope and Phase angle tracking & estimation,
o ADC antialiasing, over-, down-sampling, noise reduction techniques,
o Harmonic cancellation using FFT, harmonic current/voltage reduction/cancellation,
o Fixed & Floating point implementation,
o Motor Control and Grid-connected converter control
The course is addressed to researchers, PhD students and industry professionals from different areas i.e. renewable energy systems, electrical drives and systems, plant control, etc.
Prerequisites:
Electrical engineers and PhD students with basic knowledge about control systems, digital signal processing, modeling of dynamic systems, microcontrollers. Basic knowledge on Matlab/Simulink and C/C++ are also required.

Organizer: Associate Professor Florin Iov, fi@et.aau.dk – Aalborg University

Lecturers: Associate Professor Florin Iov, fi@et.aau.dk – Aalborg University and Postdoc Laszlo Mathe, lam@et.aau.dk – Aalborg University

ECTS: 4

Time: 24-28 March, 2014

Place: Aalborg University, Pontoppidanstræde 101

Zip code: 9220

City: Aalborg

Number of seats: 20

Deadline: 1 March, 2014

Description: With the growth and interest in collecting data through recording and capturing observational data visually, as well as orally, there is an increasing need to carefully inspect what methodological opportunities and challenges these types of qualitative data sources present to researchers. This seminar will examine and work through what it means to analyse visual and language data with the intention to pursue a qualitative study. With this in mind participants will be introduced to selected methodologies that help examine and make sense of: video and audio recordings from participant observations, photos (including participant auto-photography), the use of drawing and photos for prompted recall interviews and analysis of language derived from texts or transcripts, as well as the ethical consideration in analysing video and language.
Prerequisites: approved 2 month PhD study plan
Learning objectives: Developing the understanding, skills and competencies needed to prepare for and think about methodologies that support the analysis of visual and textual data. Specifically this includes the choice and use of particular strategies and tools for data gathering and analysis that should be related to the theoretical framework outlined. Learning outcomes will focus on particular methodologies within particular traditions and 'schools of thought' especially those that embrace and have implications for both data gathering and analysis.
Teaching methods: We adopt a dialogic style together with the course participants for discussing and working on how our different ideas may be enmeshed in the analysis design, reflect on different literature, also to demonstrate ways in which research projects develop in iterative, fluid, and often unexpected ways. Teaching methods will include group work / working in smaller groups to discuss how particular methodologies can be adopted to support the analysis of visual and textual data.
Criteria for assessment: Participants will be expected to prepare a detailed plan for the analysis procedures of their visual and/or textual research data, based on a methodologically underpinned argument that needs to be handed in two weeks after the completion of the workshop.
Key literature:
Goldman, Pea, Barron & Derry (2007). Video research in the learning sciences. Mahwah, New Jersey: Lawrence Erlbaum Associates Publishers.

Sullivan, P. (2011). Qualitative data analysis using a dialogical approach. SAGE Publications Limited.

Thomson, P. (2008). Doing visual research with children and young people. London, New York: Routledge.

Kress, G., & van Leeuwen, T. (2006). Reading images: The grammar of visual design. Second edition. New York: Routledge.

Otrel-Cass, K., Cowie, B. & Maguire, M. (2010). Taking video cameras into the classroom. Waikato Journal of Education, 15(2), 109-118.

Bernard, H. Russel (2006). Research Methods in Anthropology: Qualitative and Quantitative Approaches. 4th Edition. London: Altamira Press.

Organizer: Alyne Delaney

Lecturers: Kathrin Otrel-Cass and Alyne Delaney

ECTS: 3

Time: 9-10 April, 2014

Place: Aalborg University, Skibbrogade 5, room Skb5 b1/18

Zip code: 9000

City: Aalborg

Number of seats: 25

Deadline: 19 March, 2014

Description:
The objective of this PhD course is to provide PhD Candidates with new theories and methods within formative evaluations. Several studies evaluates a technology, product, or service during development, often iteratively, in order to make early improvements, or helps to refine or improve a technology. This is a type of evaluations that helps to form the design of the technology, product, or service. It might help in detecting and eliminating early stage problems, as well as answering questions such as which strategy can be used to improve the technology, product, or service. However this comes with many challenges, and this course will provide various theoretical- and specific methodological approaches for how to perform formative user evaluations. The course will have a special focus on how to perfrom formative user evaluations of serious games, gamification, technologies in urban and architectural design, mobility (autonomous driving), and creativity.   

Course participants will be introduced to in-depth research and foundation of how to make a successful formative user evaluations. An essential focus of the PhD course is how to perform and document solid and advanced user evaluations with improved validity and reliability. The course will also provide a theoretical foundation (definitions) and applied (how to measure) overview of concepts of e.g. mixed methods, motivation, flow, engagement, immersion, and gamification within a context of game research and development. 

Teaching methods: 
Lectures with presentation of different methodological overviews (50%). Participant presentations with added theoretical and practical discussions (25%). Workshop where participants will work in groups e.g. using new theories and methods. The groups set-up own theoretical focus (25 %).

Evaluation:   
The evaluation consists of three parts:
1. Participation all three days

2. Participation and presentation based on assigned task during the course (in groups).

3. Presentations linked to your current PhD project. The presentation must somehow have a focus within serious games/gamification. The focus can be within empirical data, ethical issues, and theoretical or even more abstract methodological questions. The duration of the presentation must not exceed 10 minutes. There will be 20 minutes for discussion. Your presentation should include a specific question/ problem you would like for discussion/ advice.

Organizer: Thomas Bjørner, Head of Media Innovation & Game Research

Lecturers:
Thomas Bjørner: Formative User Evaluations. Henrik Schønau Fog: Applied Serious Games. Thomas Bjørner: The importance of pilot testing.  Thorkild Hanghøj: Future perspective on Creativity and Learning

ECTS: 3.0

Time: 29-30 November 2022

Place: TBA

Number of seats: 18

Deadline: 8 November 2022

Important information concerning PhD courses:
We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Organizer: Dr. Subham Sahoo sssa@energy.aau.dk

Lecturers: Dr. Subham Sahoo, AAU Energy

ECTS: 2,5 ECTS

Date/Time: 30 September - 2 October 2024

Deadline: 8 September 2024

Max no. of participants: 40

Place: AAU Energy, Pontoppidanstraede 101, Aalborg, Denmark

Description: 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. All these facts 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 realtime, (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.

• Day 1: General information about cyber security and its impact on microgrids – Subham Sahoo
• Day 2: Cyber security framework for microgrids – Subham Sahoo
• Day 3: Cyber security laboratory exercise and demonstration – Subham Sahoo

Price:  6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT.
A link for online payment by credit card for externals participants will be annonced after deadline for registration

Prerequisites: Practicing knowledge in power electronic systems and control theory. Experience in using Matlab/Simulink

 Find more information about the course here

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 3000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

Price:  6000 DKK for PhD students outside of Denmark and 8000 DKK for the Industry excl. VAT.
 A Online link for externals participants will be annonced after deadline for registration

Important information concerning PhD courses: We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce 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 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. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.

The course consists of lectures and hands-on exercises, which allow the course participants to understand in-depth the technical problems related to HADs and their potential solutions. The course is multi-disciplinary, with a focus on application of theoretical results to real-world problems, and practical do's and don'ts.

The course has three main parts. The first part is a short introductory part, which lays the foundation for the rest of the course, covering fundamental topics such as auditory perception (normal and impaired hearing) and a discussion of the basic principles of HADs. The second part provides an overview of fundamental signal processing problems encountered in HADs, and an in-depth treatment of state-of-the-art solutions. These include methods for beamforming and noise reduction, direction-of-arrival estimation, voice activity detection, feedback control, hearing loss compensation, etc. Furthermore, an overview is given of methodologies for evaluating HADs with a particular focus on methods for intelligibility assessment and estimation. The third part of the course presents emerging technologies for hearing assistive devices, including machine learning techniques for processing of speech in noise, audio-visual signal processing, intelligibility prediction, user-aware/symbiotic signal processing, methods for own-voice processing, etc. While the course focuses on the HAD application, many of the discussed techniques are general and find use in the much broader field of general sound processing.

The course also bridges the gap between theoretical background and practical/robust application. The course is a one-week concentrated course to be held in the Summer, 2021. The course involves course preparation (approximately 1 ECTS), course presence (1 ECTS), assignment finalization and hand-in (1 ECTS)

Prerequisites: Basic knowledge of statistical signal processing, stochastic processes, and linear algebra. Familiarity/handy with Matlab/Python.

The course schedule is still under preparation.

Course Fee: Free for PhD students and postdocs. The fee is 7500 DKK (1000 EUR) for industrial participants.

For more information about the Summer School, feel free to contact the organizers:
Prof. Jesper Jensen (jje@es.aau.dk), Prof. Zheng-Hua Tan (zt@es.aau.dk), and Prof. Jan Østergaard (jo@es.aau.dk).

The course will be given following the guidelines of the Danish Health Authorities on the COVID-19, and will take place with physical presence of (and physical distance between) the course participants. In case the Covid-19 situation prevent us from having physical presence, an alternative online version of the course will be introduced.

Welcome to Computing with data using R

Description: Most quantitative research projects involve both case-specific programming tasks as well as data analysis of a more standard nature. When working with quantitative data it is moreover essential to be able to do so in a systematic and reproducible manner with trustworthy software. This course aims at introducing the free program R as a computational environment for integrating these tasks. R has for two decades been a leading tool for computing with data and it is the preferred language for implementation of new statistical methodology.
The course will cover the practice of scientific computing, programming, and quantitative analyses as well as the essential theoretical underpinnings.
The topics of the course will include.

• Introducing R as a statistical programming environment for data analysis.
• Efficient data management using R.
• High-level graphics in R.
• Statistical models in R
• Aspects of scientific computing in theory and practice.
• Reproducible research in practice
• Programming in R and vectorized computations.
• Optional (if time permits) Matrix factorizations and other numerical methods in R. Easy integration of C++ code in R.

Prerequisites: Participants must have a working knowledge of elementary statistical methods such as regression models and analysis of variance.

Learning objectives: After completing the course the participants will 1. be able to solve programming tasks with R. 2. know how to manage data, visualize data and fit models to data using R. 3. have learned enough about R to continue learning on their own.

Teaching methods: A combination of instructive videos, computer practicals and lectures.

Criteria for assessment: Active participation in the practicals + approval of major exercise (to be handed in after the course).

Frequently asked questions:

• Q: I am not a ph.d. student, but I would like to participate in the course anyway. Is that possible?
• A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk
• Q: If I participate in the course, can you then help me analyze a dataset that I work with as part of my ph.d. project.
• A: No, I am afraid that this is not possible
• Q: I realize that I am late for enrollment, but I would really like to participate. Is it possible.
• A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk

Organizer: Søren Højsgaard,Department of Mathematical Sciences.

All course information will be made available under http://people.math.aau.dk/~sorenh/teaching/2015-cowidur/

Lecturer: Søren Højsgaard who is associate professor at the Department of Mathematical Sciences. He has 20 years of practical experience with R. He has authored several R packages and he has written a book about qraphical models with R.

ECTS: 4

Time: 28-30 October and 4-6 November, 2015 9:00-15:30

Place: Aalborg University
28-29-30 October + 5-6 November Fibigerstræde 1/33

4 November                                         Fibigerstræde 3/31

Zip code: 9220 City: Aalborg

Number of seats: 40

Deadline: 7 October, 2015

Welcome to Computing with data using R

Description: Most quantitative research projects involve both case-specific programming tasks as well as data analysis of a more standard nature. When working with quantitative data it is moreover essential to be able to do so in a systematic and reproducible manner with trustworthy software. This course aims at introducing the free program R as a computational environment for integrating these tasks. R has for two decades been a leading tool for computing with data and it is the preferred language for implementation of new statistical methodology. The course will cover the practice of scientific computing, programming, and quantitative analyses as well as the essential theoretical underpinnings. The topics of the course will include.

• Introducing R as a statistical programming environment for data analysis.
• Efficient data management using R.
• High-level graphics in R.
• Statistical models in R
• Aspects of scientific computing in theory and practice.
• Reproducible research in practice
• Programming in R and vectorized computations.
• Optional (if time permits) Matrix factorizations and other numerical methods in R. Easy integration of C++ code in R.

Prerequisites: Participants must have a working knowledge of elementary statistical methods such as regression models and analysis of variance.

Learning objectives: After completing the course the participants will 1. be able to solve programming tasks with R. 2. know how to manage data, visualize data and fit models to data using R. 3. have learned enough about R to continue learning on their own.

Teaching methods: A combination of instructive videos, computer practicals and lectures.

Criteria for assessment: Active participation in the practicals + approval of major exercise (to be handed in after the course).

Frequently asked questions:

• Q: If I participate in the course, can you then help me analyze a dataset that I work with as part of my ph.d. project.
• A: No, I am afraid that this is not possible
• Q: I would like to participate in the course, but during a part of the course period I can not be present. Is it possible to follow to course via Skype or similar?
• A: No, I am afraid that this is not possible
• Q: I am not a ph.d. student, but I would like to participate in the course anyway. Is that possible?
• A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk
• Q: I realize that I am late for enrollment, but I would really like to participate. Is it possible.
• A: You will have to ask the doctoral school: doctoral.school@adm.aau.dk

Organizer: Søren Højsgaard, Department of Mathematical Science, email: sorenh@math.aau.dk

Lecturers: Søren Højsgaard who is associate professor at the Department of Mathematical Sciences. He has 20 years of practical experience with R. He has authored several R packages and he has written a book about qraphical models with R.

ECTS: 4

Time and place:
26, 27, 28 April 2017 Frederiks Bajers Vej 7D, room Frb 7D/2-106  and
8, 9,10 May 2017  Frederiks Bajers Vej 7C, room Frb 7C/3-204

City: 9220  Aalborg 

Number of seats: 40

Deadline: 29 March 2017

Important information concerning PhD courses We have over some time experienced problems with no-show for both project and general courses. It has now reached a point where we are forced to take action. Therefore, the Doctoral School has decided to introduce a no-show fee of DKK 5,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before 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 three months before start. This can hopefully also provide new students a chance to register for courses during the year. We look forward to your registrations.