6 papers
Control-Oriented Scenario Tree Construction through Reinforcement Learning
Fabio Pavirani, Bert Claessens, Pierre Pinson +1
Multistage stochastic model predictive control (MPC) handles uncertainty by optimizing over a scenario tree, a finite branching approximation of future outcomes constructed from sa…
S3TS: Stochastic Scenario-Structured Tree Search for Advanced Planning Under Uncertainty
Fabio Pavirani, Bert Claessens, Pierre Pinson +1
Effective scheduling in the energy sector is essential to ensure the reliable operation of electrical grids and their connected assets by, for instance, optimizing the dispatch of…
Neural Network-Assisted Model Predictive Control for Implicit Balancing
Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens +1
In Europe, balance responsible parties can deliberately take out-of-balance positions to support transmission system operators (TSOs) in maintaining grid stability and earn profit,…
Model Predictive Control-Guided Reinforcement Learning for Implicit Balancing
Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens +1
In Europe, profit-seeking balance responsible parties can deviate in real time from their day-ahead nominations to assist transmission system operators in maintaining the supply-de…
Gaming Strategies in European Imbalance Settlement Mechanisms
Seyed Soroush Karimi Madahi, Kenneth Bruninx, Bert Claessens +1
Transmission System Operators (TSOs) rely on balancing energy provided by Balancing Service Providers (BSPs) to maintain the supply-demand balance in real time. Balance Responsible…
Predicting and Publishing Accurate Imbalance Prices Using Monte Carlo Tree Search
Fabio Pavirani, Jonas Van Gompel, Seyed Soroush Karimi Madahi +2
The growing reliance on renewable energy sources, particularly solar and wind, has introduced challenges due to their uncontrollable production. This complicates maintaining the el…