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.