电力系统自动化2019，Vol.43Issue(5)：183-191,9.DOI:10.7500/AEPS20180110007
深度强化学习在需求响应中的应用
Application of Deep Reinforcement Learning in Demand Response
摘要
Abstract
With the advancement of electricity market reform in China, the demand response business is developing towards diversification and normalization. The requirements for the reliability and accuracy of demand response in the new environment are getting higher and higher, and there is an urgent need for perfect technical support. Deep reinforcement learning can make more accurate identification of complex external environments and make optimal decisions, which can exactly meet the requirements of demand response. Based on this, the application of deep reinforcement learning technology in the demand response is discussed. Firstly, the development history and research status of deep reinforcement learning are presented. Meanwhile, the research status and future development requirements of demand response are analyzed. Then the feasibility and methods of deep reinforcement learning applied to demand response services are discussed. Finally, the demand responsive business development framework based on deep reinforcement learning is proposed, and an in-depth analysis of the implementation process of deep reinforcement learning is conducted, which provides a reference for the development of demand response technologies.关键词
需求响应/深度学习/强化学习/人工智能/神经网络Key words
demand response/deep learning/reinforcement learning/artificial intelligence/neural network引用本文复制引用
孙毅,刘迪,李彬,徐永海..深度强化学习在需求响应中的应用[J].电力系统自动化,2019,43(5):183-191,9.基金项目
国家自然科学基金资助项目(51777068) （51777068）
This work is supported by National Natural Science Foundation of China (No. 51777068). （No. 51777068）
