8 citations · 17 across the 14 of their papers we have counts for
5 papers · 1 filter
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…
Control Policy Correction Framework for Reinforcement Learning-based Energy Arbitrage Strategies
Seyed Soroush Karimi Madahi, Gargya Gokhale, Marie-Sophie Verwee +2
A continuous rise in the penetration of renewable energy sources, along with the use of the single imbalance pricing, provides a new opportunity for balance responsible parties to…
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…
Explainable Reinforcement Learning-based Home Energy Management Systems using Differentiable Decision Trees
Gargya Gokhale, Bert Claessens, Chris Develder
With the ongoing energy transition, demand-side flexibility has become an important aspect of the modern power grid for providing grid support and allowing further integration of s…
Distill2Explain: Differentiable decision trees for explainable reinforcement learning in energy application controllers
Gargya Gokhale, Seyed Soroush Karimi Madahi, Bert Claessens +1
Demand-side flexibility is gaining importance as a crucial element in the energy transition process. Accounting for about 25% of final energy consumption globally, the residential…