203 citations · 220 across the 9 of their papers we have counts for
9 papers
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…
HomeLabGym: A real-world testbed for home energy management systems
Toon Van Puyvelde, Marie-Sophie Verwee, Gargya Gokhale +2
Amid growing environmental concerns and resulting energy costs, there is a rising need for efficient Home Energy Management Systems (HEMS). Evaluating such innovative HEMS solution…
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…
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…
Transfer Learning in Transformer-Based Demand Forecasting For Home Energy Management System
Gargya Gokhale, Jonas Van Gompel, Bert Claessens +1
Increasingly, homeowners opt for photovoltaic (PV) systems and/or battery storage to minimize their energy bills and maximize renewable energy usage. This has spurred the developme…
Real-World Implementation of Reinforcement Learning Based Energy Coordination for a Cluster of Households
Gargya Gokhale, Niels Tiben, Marie-Sophie Verwee +3
Given its substantial contribution of 40\% to global power consumption, the built environment has received increasing attention to serve as a source of flexibility to assist the mo…
PhysQ: A Physics Informed Reinforcement Learning Framework for Building Control
Gargya Gokhale, Bert Claessens, Chris Develder
Large-scale integration of intermittent renewable energy sources calls for substantial demand side flexibility. Given that the built environment accounts for approximately 40% of t…
Physics Informed Neural Networks for Control Oriented Thermal Modeling of Buildings
Gargya Gokhale, Bert Claessens, Chris Develder
This paper presents a data-driven modeling approach for developing control-oriented thermal models of buildings. These models are developed with the objective of reducing energy co…