7 papers · 1 filter
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…
Probabilistic forecasting of power system imbalance using neural network-based ensembles
Jonas Van Gompel, Bert Claessens, Chris Develder
Keeping the balance between electricity generation and consumption is becoming increasingly challenging and costly, mainly due to the rising share of renewables, electric vehicles…
Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks
Fabio Pavirani, Gargya Gokhale, Bert Claessens +1
To reduce global carbon emissions and limit climate change, controlling energy consumption in buildings is an important piece of the puzzle. Here, we specifically focus on using a…