Day-ahead Strategic Bidding of Renewable Energy Considering Output Uncertainty Based on Deep Reinforcement Learning
Author:
Affiliation:
1. Southeast University,School of Electrical Engineering,Nanjing,China
2. State Grid Anhui Electric Power Co., LTD,State Grid Corporation of China,Hefei,China
3. State Grid Corporation of China,China Electric Power Research Institute,Nanjing,China
Funder
Science and Technology Project of State Grid
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx8/10543251/10544378/10544921.pdf?arnumber=10544921
Reference11 articles.
1. Model-based deep reinforcement learning for wind energy bidding
2. Cooperative game-based bidding strategy and revenue distribution of clean energy-containing power producers in spot market;Lu;Electric Power Construction,2020
3. Joint equilibrium analysis of day-ahead electricity market and demand response trading market with wind power participation bidding;Wang
4. Wind power day trading strategy research based on deep reinforcement learning;Meng,2021
5. Concentrating solar power plant and wind farm joint optimization operation and bidding strategy;Fang
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