Power Systems and Markets Research Group - University of Mons (Belgium)

We are thrilled to announce that our #SALOME project proposal has been granted by the European Interreg France-Wallonie-Vlaanderen program.   #SALOME will investigate a novel scientific strategy for dynamic management and predictive maintenance of #offshore #wind turbines by taking into consideration all the physical parameters and phenomena impacting their aging in order to facilitate a fatigue-informed participation of offshore wind farms in frequency control and in electricity markets (day-ahead and reserve) .   The project brings together universities and research centres expert in modelling of atmospheric phenomena (Université du Littoral Côte d'Opale, France), developing real-time temperature and vibration sensors (Advanced Photonic Sensors, UMONS, & Applied Photonics Department, Multitel), modelling and control of wind turbines (Electrical Energy Laboratory (EELAB), Ghent University, Belgium), and in developing optimized decision-making tools for power systems and electricity markets (Power Systems and Markets Research Group - University of Mons (Belgium)). SALOME project will be led & coordinated by Faculté Polytechnique de Mons, UMONS. Thanks to the whole team involved in the preparation of the project:   Francois Vallee, Christophe Caucheteur, Bashir Bakhshideh Zad, Karima Chah, Lieven Vandevelde, Alexei Sentchev, Yves hernandez, Patrick AUGUSTIN, Hervé Delbarre, Jérémie Bottieau, Séverine Coppée. UMONS Research, Innovation & Entrepreneurship

[EN] The launching conference of SALOME Interreg FWVL project funded by the Interreg France-Wallonie-Vlaanderen program was held on the 17th of December at UMONS. During the half-day conference, we had the pleasure to bring together industry experts, researchers, and academics to discuss various aspects relating to development, integration, maintenance, and control of offshore wind turbines. Special thanks to all our speakers from SALOME project, Loïc Tilman from Elia Group, and Spyridon Iason Dizes from ENTSO-E as well as all the conference attendees.    SALOME aims to facilitate a fatigue-informed integration of offshore wind farms in the day-ahead and reserve electricity markets via a dynamic monitoring approach considering the atmospheric phenomena. For more information, please visit our website: https://lnkd.in/eiNxg9GC [FR] La conférence de lancement du projet SALOME financé par le programme Interreg FWVL s'est tenue le 17 décembre à l'UMONS. Au cours de cette conférence d'une demi-journée, nous avons eu le plaisir de réunir des experts de l'industrie, des chercheurs et des académiques pour discuter des différents aspects du développement, de l'intégration, de la maintenance et du contrôle des éoliennes offshores. Un grand merci à tous nos intervenants ainsi qu'à tous les participants à la conférence. SALOME vise à faciliter une intégration des parcs éoliens offshore tenant compte de la fatigue dans les marchés de l'électricité et de réserve via une approche de surveillance dynamique prenant en compte les phénomènes atmosphériques. Pour plus d'informations, veuillez visiter notre site web : https://lnkd.in/eiNxg9GC [NL] De lanceringsconferentie van het SALOME Interreg FWVL-project, gefinancierd door het Interreg France-Wallonie-Vlaanderen-programma, werd gehouden op 17 december bij UMONS. Tijdens de conferentie van een halve dag hadden we het genoegen om experts uit de industrie, onderzoekers en academici bijeen te brengen om de verschillende aspecten met betrekking tot ontwikkeling, integratie, onderhoud en controle van offshore windturbines te bespreken. Speciale dank aan alle sprekers van het SALOME-project en alle deelnemers aan de conferentie. SALOME streeft ernaar de vermoeidheidsgeïnformeerde integratie van offshore windparken in de day-ahead- en reserve-elektriciteitsmarkten te vergemakkelijken via een dynamische monitoringbenadering met inachtneming van atmosferische verschijnselen. Ga voor meer informatie naar onze website: https://lnkd.in/eiNxg9GC Francois Vallee, Christophe Caucheteur, Lieven Vandevelde, Bashir Bakhshideh Zad, Karima Chah, Seyyed Ahmad Hosseini, Marie Derison, Patrick Augustin, Hervé Delbarre, alexei sentchev, Yves hernandez

We are glad to invite you to SALOME Interreg FWVL launching event that will be held on the 17th of December from 2 to 5 PM at UMONS. The conference aims to provide an overview of the offshore wind projects in Belgium, Europe and showcase the possibility of offshore wind in provision of flexibility and reserve services while addressing the challenges such as mechanical burden and structural health via a tailored dynamic monitoring approach. Thanks to all speakers of the conference from SALOME project and particularly, our invited speakers Loïc Tilman (Innovation Manager at Elia) and Spyridon Iason Dizes (Project Manager Offshore Expert at ENTSO-E). PS: An interpreter will ensure the online translation of the presentations to either French or Dutch. The SALOME project is funded by the Interreg France-Wallonie-Vlaanderen program. For more info on the project, please visit https://lnkd.in/eiNxg9GC UMONS Research, Innovation & Entrepreneurship Francois Vallee, Christophe Caucheteur, Lieven Vandevelde, Bashir Bakhshideh Zad, Karima Chah, Seyyed Ahmad Hosseini, Marie Derison, Patrick Augustin, Hervé Delbarre, alexei sentchev, Yves hernandez

We have an opening for 𝗮 𝗳𝘂𝗹𝗹𝘆-𝗳𝘂𝗻𝗱𝗲𝗱 𝗷𝗼𝗶𝗻𝘁 𝗣𝗵𝗗 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 (UMONS - Prof. Zacharie De Grève, & University of Liège - Prof. Bertrand Cornélusse) on '𝗠𝗮𝗿𝗸𝗲𝘁 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝗠𝘂𝗹𝘁𝗶-𝗦𝗲𝗰𝘁𝗼𝗿 𝗟𝗼𝗰𝗮𝗹 𝗘𝗻𝗲𝗿𝗴𝘆 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝗶𝗲𝘀', funded by the EFES project ('Enhanced Flexibility in Energy Systems', Win4Excellence call). The candidate shall hold an MSc degree in engineering, preferably in electrical/electromechanical/energy engineering or in applied mathematics. Prior skills in Operations Research and Data Science applied to Electricity (and more generally Energy) Systems, as well as a good knowledge of the liberalized electricity supply chain, will be an asset. More information concerning the position in attachment. Interested candidates shall send their CV along with a motivation letter to zacharie.degreve@umons.ac.be and Bertrand.cornelusse@uliege.be. The call will close on the 18th November 2024. Thanks in advance for sharing with your respective networks.

Job alert ! Dear network, we are hiring a 4-year PhD student that would be fully funded on the European project @https://lnkd.in/eiNxg9GC The goal of the Thesis would deal with the consideration of structural ageing in the decision-making process of wind turbines participating to reserve markets. The targeted starting date for the contract is the 1st of December. Interested people can directly apply by sending their CV and motivation letter at the following e-mail address (francois.vallee@umons.ac.be)

Last week, I had the chance to attend the IEEE Power & Energy Society ISGT Europe 2024 conference in the beautiful city of Dubrovnik in Croatia! ☀ I had the opportunity to present our paper, "Decision-Focused Learning for Optimized Participation of an Industrial Consumer in Energy-Only and Reserve Markets", co-authored with Pietro Favaro, Francois Vallee, Bruno FRANCOIS, and Jean-François Toubeau. Our research focuses on bridging the gap between machine learning and decision-making in modern power systems. It investigates the concept of Decision-Focused Learning wherein the optimization model is integrated into the training pipeline of the prediction model. 📝 https://lnkd.in/eCG2UCAS I want to thank the attendees for the insightful feedback and discussions, as well as all the participants with whom I had great exchanges throughout the event. #ieeepes #ISGT #ISGTEurope

We have an opening for 𝗮 𝗳𝘂𝗹𝗹𝘆-𝗳𝘂𝗻𝗱𝗲𝗱 𝗷𝗼𝗶𝗻𝘁 𝗣𝗵𝗗 𝗽𝗼𝘀𝗶𝘁𝗶𝗼𝗻 (UMONS - Prof. Zacharie De Grève, & University of Liège - Prof. Bertrand Cornélusse) on '𝗠𝗮𝗿𝗸𝗲𝘁 𝗗𝗲𝘀𝗶𝗴𝗻 𝗳𝗼𝗿 𝗠𝘂𝗹𝘁𝗶-𝗦𝗲𝗰𝘁𝗼𝗿 𝗟𝗼𝗰𝗮𝗹 𝗘𝗻𝗲𝗿𝗴𝘆 𝗖𝗼𝗺𝗺𝘂𝗻𝗶𝘁𝗶𝗲𝘀', funded by the EFES project ('Enhanced Flexibility in Energy Systems', Win4Excellence call). The candidate shall hold an MSc degree in engineering, preferably in electrical/electromechanical/energy engineering or in applied mathematics. Prior skills in Operations Research and Data Science applied to Electricity (and more generally Energy) Systems, as well as a good knowledge of the liberalized electricity supply chain, will be an asset. More information concerning the position in attachment. Interested candidates shall send their CV along with a motivation letter to zacharie.degreve@umons.ac.be and Bertrand.cornelusse@uliege.be. The call will close on the 18th November 2024. Thanks in advance for sharing with your respective networks.

➡Massive integration of renewable resources into the electric distribution systems has led to new trends in power exchanges at the interface between Transmission & Distribution systems. ➡An accurate prediction of power exchanges at Transmission–Distribution interfaces is crucial for both the Transmission System Operators (TSOs) and the Distribution System Operators (DSOs) considering the short-term operational control and long-term planning perspectives. 💡In our new research published in the Electric Power System Research journal, we proposed a novel 𝗣𝗵𝘆𝘀𝗶𝗰𝘀-𝗜𝗻𝗳𝗼𝗿𝗺𝗲𝗱 𝗠𝗮𝗰𝗵𝗶𝗻𝗲 𝗟𝗲𝗮𝗿𝗻𝗶𝗻𝗴 (PIML) model 𝘁𝗼 𝗲𝗻𝗵𝗮𝗻𝗰𝗲 𝘁𝗵𝗲 𝗽𝗿𝗲𝗱𝗶𝗰𝘁𝗶𝗼𝗻 𝗼𝗳 𝗽𝗼𝘄𝗲𝗿 𝗲𝘅𝗰𝗵𝗮𝗻𝗴𝗲𝘀 𝗮𝘁 𝗧𝗿𝗮𝗻𝘀𝗺𝗶𝘀𝘀𝗶𝗼𝗻–𝗗𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝗶𝗻𝘁𝗲𝗿𝗳𝗮𝗰𝗲𝘀. 🎯Novelty of the proposed model lies in its combination of an Inverse Load Flow formulation, which defines an 𝗲𝗾𝘂𝗶𝘃𝗮𝗹𝗲𝗻𝘁 𝗺𝗼𝗱𝗲𝗹 𝗼𝗳 𝘁𝗵𝗲 𝗱𝗶𝘀𝘁𝗿𝗶𝗯𝘂𝘁𝗶𝗼𝗻 𝗻𝗲𝘁𝘄𝗼𝗿𝗸, 𝘄𝗶𝘁𝗵 𝘁𝗵𝗲 𝗰𝗹𝗮𝘀𝘀𝗶𝗰𝗮𝗹 𝗱𝗮𝘁𝗮-𝗱𝗿𝗶𝘃𝗲𝗻 𝗿𝗲𝗴𝗿𝗲𝘀𝘀𝗶𝗼𝗻 𝘁𝗲𝗰𝗵𝗻𝗶𝗾𝘂𝗲𝘀. ✅ Simulation results conducted on a modified version of the Oberrhein MV network highlight 𝘁𝗵𝗲 𝘀𝘂𝗽𝗲𝗿𝗶𝗼𝗿𝗶𝘁𝘆 𝗼𝗳 𝘁𝗵𝗲 𝗽𝗿𝗼𝗽𝗼𝘀𝗲𝗱 𝗣𝗜𝗠𝗟 𝗮𝗽𝗽𝗿𝗼𝗮𝗰𝗵 𝗼𝘃𝗲𝗿 𝘁𝗵𝗲 𝗳𝘂𝗹𝗹 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴-𝗯𝗮𝘀𝗲𝗱 𝗺𝗲𝘁𝗵𝗼𝗱𝘀, as demonstrated by the statistical indicators. ✅ In addition, this research adopts the TSO perspective through a 2-step Optimal Power Flow analysis that integrates power predictions and enables the calculation of production and deviation costs linked to predicted powers. 📝This research is authored by Arnaud Rosseel, Bashir Bakhshideh Zad, Francois Vallee and Zacharie De Grève from Power Systems and Markets Research Group - University of Mons (Belgium). 📝 The paper is accessible (for free over the next 50 days) at: https://lnkd.in/e6-6biWP

Job Announcement: Postdoctoral Researcher in Long-Term Offshore Wind Power Forecasting and Maintenance Scheduling ·      Deadline for applications: 1 October 2024 ·      Expected start date: ASAP ·      Duration: 7 months Note: Candidates already in Belgium or able to relocate quickly are preferred due to the project's urgent start. Position Overview: The Power System and Market Research Group at the University of Mons is seeking a highly motivated Postdoctoral Researcher to join a project on long-term wind power forecasting and maintenance scheduling. This project is in collaboration with N-Side, a leader in advanced analytics, and Elia, the Belgian transmission system operator. Notably, a well-established pipeline from data cleaning to forecasting and optimization is already in place. Accordingly, there is significant room for innovation and improvement to build upon the existing framework. Key Responsibilities: ·      Refine and improve wind power forecasting models (day-ahead to week-ahead) ·      Refine and improve optimization algorithms for offshore asset maintenance scheduling ·      Collaborate with industrial partners to apply solutions to a real-world energy challenge. ·      Publish research findings in high-impact journals and present at conferences. Qualifications: ·      PhD in Electrical Engineering, Data Science, Operations Research, or a related field. ·      Strong background in forecasting techniques and optimization methods. ·      Proficiency in programming languages such as Python, R, or Julia. ·      Excellent analytical, communication, and teamwork skills. ·      Fluency in English. Benefits: ·      Competitive salary ·      Opportunities for professional development and academic growth. Application Process: Interested candidates are invited to submit the following documents to Prof. François Vallée at francois.vallee@umons.ac.be ·      An academic CV ·      A list of publications

➡To enhance the quality of energy management tasks, accurately representing the thermal dynamics of buildings is crucial. Traditional methods aim to improve the building model in regards to an arbitrary statistical metric, before feeding the trained model to the optimization-based energy management process. 💡In a recent collaboration between the Power Systems and Markets Research Group - University of Mons (Belgium) and The University of Hong Kong, we advocate for a more integrated approach, consisting of incorporating the downstream optimization directly into the training pipeline. The goal is to improve the building model in strategic operating zones, where the greatest impact on decision-making will be achieved. 🎯To this end, we first formulate the thermal dynamics as ordinary differential equations (ODEs) using neural networks. The model parameters are then updated through an end-to-end gradient-based training strategy wherein the downstream optimization is used as the loss function. To increase the robustness of the approach, the proposed loss is combined with traditional physics-informed accuracy-oriented training, employing a novel coordinated gradient descent algorithm. ✅ Simulation results show the effectiveness of the proposed modeling method, regarding both the optimality of decisions and their physical interpretability. 📝This research recently published by the IEEE Transactions on Smart Grid is authored by Xueyuan Cui, Jean-François Toubeau, Francois Vallee, and Wang Yi. 📝The full paper is accessible here: https://lnkd.in/eYQWgKCC