DTU PES Summer School 2025
Future Energy Systems: Leveraging Advanced Optimization, Data Sharing and AI for Market Design and Operation
The DTU PES Summer School 2025 took place from the 18th – 23rd of May 2025. The school was an intensive 5 day course looking to teach participants all about novel research topics and methods in power systems. The school included talks by world-renowned researchers and leading industrial companies in the field of power systems. Participants earned 2.5 ECTS by attending the school and submitting a summary of their learnings after completing the summer school.
Program
Speakers
Paul Joskow
Paul Joskow is the Elizabeth and James Killian Professor of Economics at the Massachusetts Institute of Technology (MIT) and President emeritus of the Alfred P. Sloan Foundation. Joskow has been on the MIT faculty since 1972, where he was the head of the MIT Department of Economics from 1994 to 1998 and director of the MIT Center for Energy and Environmental Policy Research from 1999 to 2007. Joskow became president of the Sloan Foundation in 2008 and returned to MIT in 2018. At MIT his teaching and research areas include industrial organization, energy and environmental economics, competition policy, and government regulation of industry. He is a past-president of the International Society for New Institutional Economics, a distinguished fellow of the Industrial Organization Society, a distinguished fellow of the American Economic Association, a fellow of the Econometric Society, a fellow of the American Academy of Arts and Sciences, a fellow of the Econometric Society, and a member of the Council on Foreign Relations. He has served on the boards of the New England Electric System, National Grid PLC, TC Energy, State Farm Indemnity, Putnam Mutual Funds, Exelon Corporation, and the Whitehead Institute for Biomedical Research (current).
Richard O’Neill
Dr. Richard O’Neill currently serves as a Distinguished Senior Fellow at the Advanced Research Projects Agency – Energy (ARPA-E). Prior to his time at ARPA-E, O’Neill served as the Chief Economic Advisor at the Federal Energy Regulatory Commission (FERC) and as the Director of FERC’s Office of Pipeline and Producer Regulation. During his time at FERC, O’Neill led the Chairman’s teams to develop policy and restructure the natural gas and the electric power markets, develop oil-pipeline rate index by benchmarking to actual industry costs, and increase the efficiency of FERC’s market software. Further, O’Neill led a group that developed transmission switching software that would ultimately become an ARPA-E project and was integral to the initial design of ARPA-E’s Grid Optimization Competition. Previously, he was Director of the Office of Economic Policy and Office of Pipeline and Producer Regulation. From 1978 to 1986, he directed oil and gas analysis and forecasting at the Energy Information Administration. From 1973 to 1978, he was on the Louisiana State University computer science faculty. From 1969 to 1973, he was on the University of Maryland business school faculty. He has a B.S. in chemical engineering, an MBA and a Doctorate in operations research from the University of Maryland. He is a Fellow of INFORMS and an Associate Researcher in the University of Cambridge Energy Policy Research Group. In 2016, he received the International Association of Energy Economics Outstanding Contributions to Energy Economics Award. His work with governments and companies has included mathematical software, energy modeling, forecasting, open access, restructuring, competition, performance-based regulation, market power mitigation and market design. His work has appeared in journals and books in Applied Mathematics, Optimization, Operations Research, Computer Science, Energy, Electrical Engineering, Economics, and Law.
Natalia Fabra
Natalia Fabra is Professor of Economics at Carlos III University. She is a Research Fellow at the Centre for Economic Policy Research and CESifo. She is an Associate Member of the Toulouse School of Economics and Cemfi. She belongs to the Economic Advisory Group on Competition Policy (EAGCP) of the European Commission. She obtained her Ph.D. in 2001 at the European University Institute (Florence) under the supervision of Prof. Massimo Motta. Natalia works in the field of Industrial Organization, with an emphasis on Energy and Environmental Economics and Regulation and Competition Policy. She has published her research papers in leading journals such as the American Economic Review, Management Science, The Rand Journal of Economics, The Economic Journal, Energy Economics, The Journal of Industrial Economics, and the International Journal of Industrial Organization, among others. Natalia is an Associate Editor at the Economic Journal, the Journal of the European Economic Association, and the International Journal of Industrial Organization, and belongs to the Scientific Council of Bruegel. In 2014, Natalia received two distinguished awards as Spanish Best Young Economist (one awarded by the Banco Sabadell Foundation and the other by the Madrid regional government). In 2017, she was awarded an ERC Consolidator grant “Current Tools and Policy Challenges in Electricity Markets”, for 2018-2024. She has also been awarded an ERC Advanced grant “Socio-Economic Challenges and Opportunities of the Energy Transition (ENERGY-IN-TRANSITION)”, for 2025-2030. Natalia has been a Research Visiting Fellow at several institutions, including the University of California Energy Institute (Berkeley), Nuffield College (Oxford), the Toulouse School of Economics, and Northwestern University (Chicago), among others. Currently, Natalia is an independent board member of the Spanish gas TSO, President of the European Association for Research in Industrial Economics (EARIE), and Past-President of the Spanish Economic Association (AEE).
Jochen Cremer
Dr. Jochen Cremer is the Co-Director of the TU Delft AI Energy Lab and an Associate Professor at the Faculty of Electrical Engineering, Mathematics, and Computer Science. Jochen’s research focuses on applying machine learning and data analytics to energy systems operation and control. His team develops new computational methods for system operation and control that combine statistical machine learning and mathematical optimisation.
Azarakhsh Malekian
Azarakhsh Malekian is a Professor of Operations Management at the Rotman School of Management. Her research interests include network and data economics, mechanism design, game theory, combinatorial optimization, and randomized algorithms.
Bissan Ghaddar
Bissan Ghaddar is a Professor of Management Science and Sustainability at the Ivey Business School, working on problems at the intersection of machine learning and optimization models. She is also a Professor of the Department of Technology, Management, and Economics at the Technical University of Denmark. Prior to joining Ivey Business School and DTU, she was an Assistant Professor in Data Analytics at the Department of Management Sciences at the University of Waterloo. She has also worked on energy, water, and transportation network optimization at IBM Research and on inventory management problems at the Centre for Operational Research and Analysis, Department of National Defence Canada.
Bissan was invited for extended research visits, most recently at ESSEC Business School and Politecnico di Milano. Dr. Ghaddar received a Ph.D. degree in operations research from the University of Waterloo, Canada. Her work has been published in prestigious journals such as Mathematical Programming, SIAM Journal on Optimization, Transportation Research, among others. Her research has been supported by national and international grants including NSERC, Cisco, H2020, and FP7 IIF European Union Grant. She currently works with organizations on sustainability and digitalization challenges across the aerospace, energy, manufacturing, transport, and telecommunications industries, and has facilitated strategic planning and training for various organizations internationally.
Jalal Kazempour
Jalal Kazempour is a Professor and Head of Section for Energy Markets and Analytics in the Department of Wind and Energy Systems at the Technical University of Denmark, Denmark. He received his M.Sc. degree in Electrical Engineering from Tarbiat Modares University, Iran, and his Ph.D. degree in Electrical Engineering from the University of Castilla-La Mancha, Spain. After his PhD he spent time as a postdoctoral researcher at John Hopkins University. Following this he moved to the Technical University of Denmark as a postdoctoral research and has since progressed to his current position. His research interests lie in data-driven and market-oriented approaches to power system operation and planning, also in coordination with other energy systems. His focus area is the intersection of optimization, control, game theory, and machine learning for energy applications.
Spyros Chatzivasileiadis
Spyros Chatzivasileiadis is a Professor and Head of Section for Power Systems at the Department of Wind and Energy Systems at the Technical University of Denmark. He received a Diploma in Electrical and Computer Engineering from the National Technical University of Athens, Greece, and a Ph.D. degree in Electrical Engineering from ETH Zurich. He previously was a postdoctoral researcher at the Lawrence Berkeley National Laboratory followed by time as a postdoctoral researcher at the Massachusetts Institute of Technology. His research interests lie at the cross-section of AI, control, optimization and dynamic systems to ensure the secure operation of electric systems with 100% renewable sources.
Lesia Mitridati
Lesia Mitridati is an Assistant Professor in the Department of Wind and Energy Systems at the Technical University of Denmark, Denmark. She received the M.Sc. degree in Science and Executive Engineering from Mines Paristech and her Ph.D. degree in Electrical Engineering from the Technical University of Denmark. She has spent time as a postdoctoral researcher at the Georgia Institute of Technology and ETH Zürich. Her research focuses on the interface of machine learning and data-driven optimization, with specific interest in the areas of market design for integrated energy systems, flexibility services, local energy communities, and data analytics.
Licio Romao
Licio Romao is an Assistant Professor in the Department of Wind and Energy at the Technical University of Denmark. Before joining DTU, he held postdoctoral research positions at Stanford University and the University of Oxford. He obtained his PhD in Engineering Science from the University of Oxford; MSc in Electrical Engineering from the University of Campinas (UNICAMP), Brazil; and BSc in Electrical Engineering from the Federal University of Campina Grande (UFCG), Brazil. His research leverages statistics, probability, control theory, and formal methods tools to design certified decision-making frameworks and feedback control loops for electric systems operating under 100% renewable sources.
Speakers’ slides
Introduction
Richard O’Neill
Paul Joskow
Bissan Ghaddar
Jochen Cremer
Azarakhsh Malekian
Introduction to Workshop
Lesia Mitridati and Jalal Kazempour
Spyros Chatzivassileiadis
Licio Romao
Natalia Fabra
Best poster presentations
Maria Margarida Mascarenhas
POSTER
Poster from the poster session held during the Summer School
| Poster number | Name | Keywords | Title |
|---|---|---|---|
| 1 | Harry Thawley | Energy systems; Modelling to Generate Alternatives; MGA; metaheuristics; Optimization; MINLP | Metaheuristic modelling to generate alternatives in non-linear energy system models |
| 2 | Yanlin Jiang | Flexibility Aggregation, Distribution Networks, Integrated Transmission and Distribution (ITD) System Coordination | Enhanced Flexibility Aggregation for LinDistFlow |
| 3 | Ruohong Liu | Building Energy Management; Multi-Objective Reinforcement Learning | Multi-Objective Reinforcement Learning for Building Energy Management |
| 4 | Solène Delannoy-Pavy | Maintenance Optimization, Markov Decision Process, Model uncertainty | Estimating Maintenance Costs of Offshore Electrical Substations under Uncertainty |
| 5 | Abhishek Tiwari, Ahmad Usman Khan | Transmission system planning, optimisation, green hydrogen, net-zero system operation, offshore wind | Net Zero Network: Achieving an Irish shade of green by 2050 |
| 6 | Noah Monz | “Resilience”, “Energy Storage Systems”, “Transmission Expansion Planning”, “Stochastic Dual Dynamic Programming”, and ” Cost Benefit Analysis” | Economic Threshold of Local Resilience in the Context of Constraint Transmission Line Capacity |
| 7 | Lukas Karkossa | long term energy system planning, climate change, resilience, PyPSA-EUR | Modeling highly renewable energy systems under extreme weather events |
| 8 | Etienne Cuisinier | techno-economic models, capacity expansion, adequacy, model linking, surrogate modeling, machine learning | The MuESSLi project – Multi-Energy System Smart Linking |
| 9 | Sara Querido | Power Systems, Optimization, Coordination, Interoperability | REMEDIAL ACTION OPTIMIZATION AS PART OFTHE COORDINATED SECURITY ANALYSISSERVICE AT NORDIC RCC |
| 10 | ALAN ORTIZ CONTRERAS | Conic Programming Formulation for Optimal Hybrid Sizing in AC Grids | |
| 11 | Ibtissam Hamdane | Short-term electricity markets; Reserve dimensioning ; Reserve procurement ; Market design ; Bidding strategy | Dimensioning and procurement of reserves in the context of an evolving energy mix and European harmonization |
| 12 | Maurizio Vassallo | LV Distribution Network DER Integration Long-Term Optimization Investment Decision-Making | Unified Decision-Making Framework in LV Distribution Systems: Combining Short-Term Operations and Long-Term Planning |
| 13 | Bobby Xiong | open-source, energy system modelling, policy targets, infrastructure, resilience, hydrogen, carbon, Europe | The Role of PCI-PMI Infrastructure in Reaching Europe’s Energy Policy Targets |
| 14 | Irina Zettl | ancillary services, dynamic grid support, inverter based resources, reactive power provision, voltage control | Reactive Power Provision from Inverter Based Resources in Future Power Grids |
| 15 | Marcel Sole Avila | How Inefficient Can An Electricity Market Be? | |
| 16 | Tomas Valencia Zuluaga | Peer-to-peer electricity markets, Community choice aggregation, Linear cooperative games, Statistical learning | Stable and fair uniform price allocations of community choice aggregation gains in retail electricity markets |
| 17 | Bastian Weißenburger | Hydrogen wholesale prices, market modeling, optimization | From costs to wholesale prices for green hydrogen – A case study for Europe and the MENA region |
| 18 | Erdi Saruhan | Battery Storage Optimization, HVDC Interconnectors, Cross-Border Energy Trading, Multi-stage Optimization, Value Stacking | Risk-based Operational Models for Hybrid Offshore Interconnectors for Ancillary Service Provision |
| 19 | Tommaso Ferrucci | renewable energy communities; flexibility; public private partnership | Optimization of Renewable Energy Communities for flexibility services |
| 20 | Valgerdur Jónsdóttir | Balancing Reserves, Day-Ahead Market, Hydropower Optimization, Renewable Energy, Reserve Allocation | Impact from Different Reserve Allocation Strategies in Hydropower Systems |
| 21 | NATALIA NAVAL | Pumped hydro storage, renewable energy, optimization, management, electricity markets | INTEGRATION OF LOCAL RENEWABLE ENERGY PRODUCTION WITH ENERGY STORAGE SYSTEMS FOR SUPPLYING ELECTRICITY TO INDUSTRIAL CONSUMERS |
| 22 | Zhenhua Zhang | Electricity market, negative prices, energy storage, market power, strategic behaviors | Negative Electricity Prices and Strategic Energy Storage Resources |
| 23 | Noé Diffels | Electric Vehicles, Energy Communities, Market Design, Mobility, Optimization | Market design in Multi-sectoral Energy Communities, with a focus on Mobility |
| 24 | Janik Pinter | Battery Scheduling, Stochastic Optimization, Flexibility Provision, Uncertainty Quantification, Prosumer Integration | Probabilistic Day-Ahead Battery Scheduling based on Mixed Random Variables |
| 25 | Helen Saragih | resilience, multi-timescale optimization, machine learning, electricity markets, heat and electricity systems | Multi-Timescale Production Planning of Integrated Heat and Electricity Systems Participating in Electricity Markets |
| 26 | Arman Zarrin | Multi-period security-constrained optimal power flow, power system security, sensitivity analysis, sequential linear programming, trust region | Solving Multi-Period SCOPF Using Sensitivities and Sequential Linear Approximation |
| 27 | Heidi Nielsen | MPC, Data-driven predictive control, Building energy management, Behavioral system theory, energy optimization | From Models to Data: Smarter Predictive Control in Buildings |
| 28 | Betül Mamudi | Distribution System State Estimation, Machine Learning, Uncertainty | Learning to Observe the Grid |
| 29 | Ali Kaboli | Physics-informed neural network, Reduced order model, Electric water heater, Temperature prediction, Demand response | Physics-informed neural network-based reduced order electric water heater modeling for demand response |
| 30 | Leila Shams Ashkezari | Heavy-duty electric vehicle charging, energy management, reinforcement learning, smart charging, energy hubs | RL-Based EMS for Energy Hubs with Heavy-Duty Electric Vehicle Chargers |
| 31 | Maryam Fetanat | Learning methods, linear programming, computation | AI-Based Electricity Markets |
| 32 | María de los Ángeles Sánchez Galván | Reactive Power Markets, Ancillary Services, Nash–Cournot Equilibrium, Strategic Bidding, Bi-level Optimization, MPEC/EPEC Models, Multi-Agent Reinforcement Learning (MARL), Game Theory in Power Systems, Voltage Support | From Equilibrium Models to Learning Agents: A strategic view of reactive power markets |
| 33 | Jalal Faraji | Probabilistic Forecasting of Load Demand and Low-Carbon Technologies for Enhancing Flexibility in Energy Communities | |
| 34 | Yangze Zhou | Decision-focused learning, continual learning, probabilistic forecasting, distributionally robust optimization, local energy communities | Decision-focused Learning for Local Energy Communities Management Under Uncertainty |
| 35 | Hussein Jaffal | Dynamic Modelling, Physics-Informed Neural Networks, Interpretability, Laboratory Validation | A Trustworthy Physics-Informed Neural Networks Approach for Dynamic Modelling of Converters |
| 36 | savvas panagi | Fast Frequency Response, Low Inertia, Modelling, Operation | Fast Frequency Response on a Low-inertia Power Systems |
| 37 | Pietro Favaro | Decision-Focused Learning, Constraint Learning, Online Feedback Optimization, Energy Management System | Stop Guessing, Start Optimizing: How Decision-Focused Learning Makes HVAC Smarter and Cheaper |
| 38 | Sarra Bouchkati | Residual Reinforcement Learning, Voltage Control, Machine Learning, Predictive Mainbtenance | Machine Learning Applications in Active Electric Distribution Grids |
| 39 | Maria Margarida Mascarenhas | Transparency, ENTSO-E, data, forecast, energy transition | Transparency++: Bringing More Transparency to the ENTSO-E TP Data and Forecasts |
| 40 | Ada Canaydin | Smart meter data, distributed energy resources, feature extraction, building categorisation | Feature-based Identification of Distributed Energy Resources in Buildings from Aggregated Smart Meter Data |
| 41 | Ignacio Martinez | energy crisis, energy markets, electricity markets, energy transition, and competitiveness | Energy markets in the European Union: Update on the energy crisis and recent developments |
| 42 | Chidera Abonyi | Forecast, Grid Security Analysis, Power Flow Calculation, Benchmark Grid Models | Benchmarking forecast modelling algoritms of grid dynamic data usin a benchmark European transmission grid model |
| 43 | Yago del Barrio Álvarez | Green Corporate Procurement, Efficient Mitigation, Temporal Matching, Spatial Matching, Additionality, Bilevel Modeling | How to Procure Green Power for Real Emissions Reductions? |
| 44 | Tim Kopka | Resource Adequacy, Reliability, Risk Profile, Australia | Resource Adequacy in Low-Carbon Energy Systems |
| 45 | Mohammadhassan Bahmani | ||
| 46 | Rebecca Schill, Cecilia Rorai | Decarbonisation, Energy transition, Energy system modelling, Pypsa-Eur, sector-coupling modelling, European Union, CO2 cap | Decarbonisation of the heating and power sectors of the European Union |
| 47 | Graham McClone | Hungarian Algorithm, Probabilistic Forecasting, Electricity Consumption, Short-term Load Forecasting, kNN | Short-Term Probabilistic Forecasting of Individual Household Electricity Consumption Using the Hungarian Algorithm |
| 48 | Wadaed Uturbey | Demand response (DR), Behavioral economics, Prospect Theory (PT), Consumer behavior | Behavioral Economics Perspective for Demand Response in Energy Systems |
| 49 | Natalia Gonzalez | Carbon Capture and Sequestration (CCS), Decarbonization, Capacity Expansion Planning, Criteria Air Pollution, Environmental Equity | The Use of Carbon Capture in Decarbonizing the Power Sector Increases Health Costs and Perpetuates Inequities. |
| 50 | Giulia Taromboli | energy community, power purchase agreements, bi-objective optimization | Community-based Energy Contracts for Urban Districts Decarbonization |
| 51 | Yu-Hsuan Li | Fortum’s vision and summary of field work | |
| 52 | Jonas Petzschmann | Optimisation of trading for renewable energy systems in combination with battery storage systems using reinforcement learning | |
| 53 | Gaetano Formato | Methodology for the temporal progression for the Italian Storage Need (MACSE) |