3 papers
eess.SY2025
DALNet: A Denoising Diffusion Probabilistic Model for High-Fidelity Day-Ahead Load Forecasting
Han Guo, Ding Lin
Accurate probabilistic load forecasting is crucial for maintaining the safety and stability of power systems. However, the mainstream approach, multi-step prediction, is hindered b…
eess.SY2025
A Deep Reinforcement Learning Method for Multi-objective Transmission Switching
Ding Lin, Jianhui Wang, Tianqiao Zhao +1
Transmission switching is a well-established approach primarily applied to minimize operational costs through strategic network reconfiguration. However, exclusive focus on cost re…
eess.SY2025
Reinforcement Learning Based Symbolic Regression for Load Modeling
Ding Lin, Han Guo, Jianhui Wang +2
With the increasing penetration of renewable energy sources, growing demand variability, and evolving grid control strategies, accurate and efficient load modeling has become a cri…