26 citations · 112 across the 36 of their papers we have counts for
9 papers · 1 filter
SAVGO: Learning State-Action Value Geometry with Cosine Similarity for Continuous Control
Stavros Orfanoudakis, Pedro P. Vergara
While representation and similarity learning have improved the sample efficiency of Reinforcement Learning (RL), they are rarely used to shape policy updates directly in the action…
Topology-Aware Graph Reinforcement Learning for Energy Storage Systems Optimal Dispatch in Distribution Networks
Shuyi Gao, Stavros Orfanoudakis, Shengren Hou +2
Optimal dispatch of energy storage systems (ESSs) in distribution networks involves jointly improving operating economy and voltage security under time-varying conditions and possi…
SmartMeterFM: Unifying Smart Meter Data Generative Tasks Using Flow Matching Models
Nan Lin, Yanbo Wang, Jacco Heres +2
Smart meter data is the foundation for planning and operating the distribution network. Unfortunately, such data are not always available due to privacy regulations. Meanwhile, the…
GNN-DT: Graph Neural Network Enhanced Decision Transformer for Efficient Optimization in Dynamic Environments
Stavros Orfanoudakis, Nanda Kishor Panda, Peter Palensky +1
Reinforcement Learning (RL) methods used for solving real-world optimization problems often involve dynamic state-action spaces, larger scale, and sparse rewards, leading to signif…
RL-ADN: A High-Performance Deep Reinforcement Learning Environment for Optimal Energy Storage Systems Dispatch in Active Distribution Networks
Shengren Hou, Shuyi Gao, Weijie Xia +3
Deep Reinforcement Learning (DRL) presents a promising avenue for optimizing Energy Storage Systems (ESSs) dispatch in distribution networks. This paper introduces RL-ADN, an innov…
Transformer-based few-shot learning for modeling Electricity Consumption Profiles with minimal data across thousands of domains
Weijie Xia, Gao Peng, Chenguang Wang +3
Electricity Consumption Profiles (ECPs) are crucial for operating and planning power distribution systems, especially with the increasing number of low-carbon technologies such as…