no code implementations • 28 Nov 2023 • Yang Li, Wenjie Ma, Yuanzheng Li, Sen Li, Zhe Chen
Simulation results demonstrate that our method is capable of adequately addressing the uncertainties resulting from RES and loads, mitigating the impact of cyber-attacks on the scheduling strategy, and ensuring a stable demand supply for various energy sources.
no code implementations • 26 Sep 2023 • Yuanzheng Li, Xinxin Long, Yang Li, Yizhou Ding, Tao Yang, Zhigang Zeng
In this context, unreasonable profit distributions on the demand-supply side would lead to the conflict of interests and diminish the effectiveness of cooperative responses.
no code implementations • 7 Aug 2023 • Yang Li, Shitu Zhang, Yuanzheng Li, Jiting Cao, Shuyue Jia
Deep learning has emerged as an effective solution for addressing the challenges of short-term voltage stability assessment (STVSA) in power systems.
no code implementations • 29 Dec 2022 • Yuanzheng Li, Shangyang He, Yang Li, Yang Shi, Zhigang Zeng
Then, these local models are periodically uploaded to a server and their parameters are aggregated to build a global agent, which will be broadcasted to MGs and replace their local agents.
no code implementations • 27 Dec 2022 • Yang Li, Fanjin Bu, Yuanzheng Li, Chao Long
Multi-uncertainties from power sources and loads have brought significant challenges to the stable demand supply of various resources at islands.
no code implementations • 2 Nov 2022 • Yang Li, Ruinong Wang, Yuanzheng Li, Meng Zhang, Chao Long
To handle the data privacy and openness, we propose a forecasting scheme that combines federated learning and deep reinforcement learning (DRL) for ultra-short-term wind power forecasting, called federated deep reinforcement learning (FedDRL).
no code implementations • 17 Apr 2022 • Yuanzheng Li, Shangyang He, Yang Li, Leijiao Ge, Suhua Lou, Zhigang Zeng
This paper tackles this issue by proposing a reinforcement learning assisted deep learning framework for the probabilistic EVCS charging power forecasting to capture its uncertainties.
no code implementations • 24 Feb 2021 • Zhuoling Li, Haohan Wang, Tymoteusz Swistek, Weixin Chen, Yuanzheng Li, Haoqian Wang
Few-shot learning is challenging due to the limited data and labels.