23 citations · 100 across the 12 of their papers we have counts for
5 papers · 1 filter
Interpretable Kolmogorov-Arnold Network with Feature-Isolated Temporal Attention Mechanism for Electricity Load Forecasting
Jinhao Li, Hao Wang
Accurate electricity load forecasting is a crucial prerequisite for stable power system operations. While prevalent deep learning models present competitive performance, they often…
A Unified Variational Imputation Framework for Electric Vehicle Charging Data Using Retrieval-Augmented Language Model
Jinhao Li, Hao Wang
The reliability of data-driven applications in electric vehicle (EV) infrastructure, such as charging demand forecasting, hinges on the availability of complete, high-quality charg…
A Multi-View Multi-Timescale Hypergraph-Empowered Spatiotemporal Framework for EV Charging Forecasting
Jinhao Li, Hao Wang
Accurate electric vehicle (EV) charging demand forecasting is essential for stable grid operation and proactive EV participation in electricity market. Existing forecasting methods…
Optimal Energy Storage Scheduling for Wind Curtailment Reduction and Energy Arbitrage: A Deep Reinforcement Learning Approach
Jinhao Li, Changlong Wang, Hao Wang
Wind energy has been rapidly gaining popularity as a means for combating climate change. However, the variable nature of wind generation can undermine system reliability and lead t…
Deep Reinforcement Learning for Optimal Power Flow with Renewables Using Graph Information
Jinhao Li, Ruichang Zhang, Hao Wang +3
Renewable energy resources (RERs) have been increasingly integrated into large-scale distributed power systems. Considering uncertainties and voltage fluctuation issues introduced…