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cs.LG2024
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…
cs.LG2024
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…
cs.LG2024★ 4 cited
A Flow-Based Model for Conditional and Probabilistic Electricity Consumption Profile Generation and Prediction
Weijie Xia, Chenguang Wang, Peter Palensky +1
Residential Load Profile (RLP) generation and prediction are critical for the operation and planning of distribution networks, especially as diverse low-carbon technologies (e.g.,…