Pruning-Based Knowledge Transfer Method for Power System Scheduling

Author:

Yan Zhen1,Tang Hao1,Fang Daohong1,Tan Qi1,Wang Song2,Wang Tongwen2

Affiliation:

1. School of Electrical Engineering and Automation, Hefei University of Technology,China

2. State grid Anhui Electric power Co., LTD,China

Publisher

IEEE

Reference10 articles.

1. A nash game model of multi-agent participation in renewable energy consumption and the solving method via transfer reinforcement learning;Li,2019

2. Optimization algorithm of reinforcement learning based knowledge transfer bacteria foraging for risk dispatch;Han;Automation of Electric Power Systems,2017

3. Active and reactive power coordinated optimal dispatch of networked microgrids based on distributed deep reinforcement learning;Ju;Automation of Electric Power Systems,2023

4. Optimal scheduling of regional integrated energy system based on advantage learning soft actor-critic algorithm and transfer learning;Luo;Power System Technology,2023

5. Dispatching optimization of power system with flexible resources by deep transfer reinforcement learning;Tang,2024

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