The class will take place every Friday from 8:30am till 12:30am. Due to the COVID-19 crisis, the class will be given on-line. Please check the website regularly to get all the information concerning the class (infos for connecting to the class, assignments, etc).
Module 1: Power sharing in DC microgrids
Lecturer: Bertrand Cornélusse
Supporting material can be found on the eCampus page of the course
Lecture 1: DC microgrid modelling (05-02-2021)
- Introduction to DC microgrids modelling (45 minutes),
- Power / voltage control
- Short presentation of 3 papers we want you to read and present for the next courses by group of 2 (15 minutes)
- Gan, L., & Low, S. H. (2014). Optimal power flow in direct current networks. IEEE Transactions on Power Systems, 29(6), 2892–2904. https://doi.org/10.1109/TPWRS.2014.2313514
- Wang, Z., Liu, F., Chen, Y., Low, S. H., & Mei, S. (2019). Unified Distributed Control of Stand-Alone DC Microgrids. IEEE Transactions on Smart Grid, 10(1), 1013–1024. https://doi.org/10.1109/TSG.2017.2757498
- Dragicevic, T., Lu, X., Quintero, J. C. V., & Guerrero, J. M. (2016). DC Microgrids – Part I: A Review of Control Strategies and Stabilization Techniques. IEEE Transactions on Power Electronics, 31(7), 4876 – 4891. https://doi.org/10.1109/TPEL.2015.2478859
- Hands on session:
- Introduction to modelling in Typhoon HIL (90 minutes)
- Please install Typhoon HIL before this session, see eCampus for instructions.
Lecture 2: Optimization, optimal power flow (12-02-2021)
- Introduction to LP, MILP, NLP (60 minutes)
- Optimal power flow in DC microgrids (30 minutes)
- Hands on session:
- Tiny exercises in Python/Pyomo (90 minutes)
- One or two practical optimization problem examples (30 minutes)
- Please install Python/pyomo before this session, see eCampus for instructions.
Lecture 3: Supervisory control for DC microgrids (19-02-2021)
- Presentation of papers by students (120 minutes total with breaks and discussions)
- Let’s put the first-two lectures together to do supervisory control for DC microgrids
(60 minutes) and demo by Bertrand Cornélusse
Module 2: Planning and operation of distribution network
Lecturers: Prof. Damien Ernst, Alizera Bahmanyar, David Vangulick.
Lectures will be given through the Webex platform, using the following link: https://uliege.webex.com/meet/dernst
Lecture 1: Introduction to distribution networks. Modelling and tools for the planning and operation of distribution network (26-02-2021) – Alizara Bahmanyar and Prof. Damien Ernst
Topics that will be addressed during this first class: (i) modelling of the electrical distribution network (ii) power flow analysis (iii) state estimation (iv) protections of distribution networks.
Lecture 2: Using load-flows and state estimation for the planning and operation of distribution network (05-03-2021) – David Vangulick and Prof. Damien Ernst
In this class, we will review how load-flow and state-estimation tools are currently used for operating and managing distribution networks. Technical difficulties for using them will also be analyzed (need for pseudo-measurements, difficulties associated with the IT infrastructure, etc). The class will also explain how to use Pandapower for running load-flows and state-estimations. The class will end with a description of an advanced operational planning scheme currently used in the Belgian electrical distribution industry.
Lecture 3: Adanced methods for operating and planning distribution networks (12-03-2021). Prof. Damien Ernst
During this class, students will have to present three papers related to the advanced analysis, operation and planning of distribution networks. All the papers will be put on the website one week before the class and will have to be read/study by all the students of the class. Group of maximum three students for presenting one paper. Here are the three default papers:
New papers can be suggested by the students but have to be approved by Prof. Ernst before.
Module 3: Reliability management of bulk electric power systems
Lecturers: Louis Wehenkel and Efthymios Karangelos
The logistics for teaching will be chosen at a later stage, depending on the evolution of the general situation. Links to reading material and slides will be added below, for each lecture.
Lecture 1: The classical concept of operational power systems security (19-03-2021). Louis Wehenkel
- The notions of contingency and of power system response to contingencies
- The Dy Liacco state diagram for power system operation
- The N-1 reliability standard for power system operation
- The SCOPF formulation of the preventive vs corrective security control tradeoff
- Implications for operation planning, asset management and system development activities
Lecture 2: Towards a consistent probabilistic risk management approach (26-03-2021). Efthymios Karangelos
- Motivation: what’s missing in the N-1 approach?
- Risk-based real-time operation: how to account for the (low) likelihood and potential impact of contingencies?
- Planning under uncertainty: how to tackle the daily randomness of renewable power generation?
- The need for resilience: what can go wrong will go wrong?
Lecture 3: Cyber-physical risk management of the bulk electric energy supply system (02-04-2021). LW & EK
Ahead in time the students will be provided with a list of papers on cyber-physical security of electric power systems, and by groups of two students they will prepare a 15 minutes presentation of one of these papers (choice based on the first-come/first-served basis)
- Student presentations per group/paper: 15 minutes presentation + 15 minutes questions and answers for each paper
- Open discussions about current research challenges for cyber-physical risk management
Module 4: Sustainable organisation, integration, and migration
Lecturers: BC, DE, EK, LW
The last part of the course aims at getting the big picture by understanding how the overall system, coupling microgrids, distribution grids, and transmission grids, can function, be organised, and evolve so as to co-optimise competing targets, such as reliability, environmental acceptability, societal fairness, and economic attractiveness.