[HTML][HTML] Reinforcement learning model-based and model-free paradigms for optimal control problems in power systems: Comprehensive review and future directions
E Ginzburg-Ganz, I Segev, A Balabanov, E Segev… - Energies, 2024 - mdpi.com
This paper reviews recent works related to applications of reinforcement learning in power
system optimal control problems. Based on an extensive analysis of works in the recent …
system optimal control problems. Based on an extensive analysis of works in the recent …
Learning the Optimal Power Flow: Environment Design Matters
To solve the optimal power flow (OPF) problem, reinforcement learning (RL) emerges as a
promising new approach. However, the RL-OPF literature is strongly divided regarding the …
promising new approach. However, the RL-OPF literature is strongly divided regarding the …
Market abstraction of energy markets and policies-application in an agent-based modeling toolbox
In light of emerging challenges in energy systems, markets are prone to changing dynamics
and market design. Simulation models are commonly used to understand the changing …
and market design. Simulation models are commonly used to understand the changing …
[PDF][PDF] Digitalized Energy Systems Carl von Ossietzky Universität Oldenburg Ammerländer Heerstraße 114-118, 26129 Oldenburg, thomas. wolgast@ uni-oldenburg …
T Wolgast - researchgate.net
ABSTRACT The design of Reinforcement Learning (RL) environments has a strong impact
on RL training performance and generality of results. While most researchers focus on the …
on RL training performance and generality of results. While most researchers focus on the …