Federated Multi-Agent Deep Reinforcement Learning Approach via Physics-Informed Reward for Multi-Microgrid Energy Management

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.

energy management Federated Learning +4

Probabilistic Charging Power Forecast of EVCS: Reinforcement Learning Assisted Deep Learning Approach

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.

reinforcement-learning Reinforcement Learning (RL) +2