Open AccessResearch on demand response strategy of the electricity deviation assessment
Author(s) -
Song Sibo,
Guo Hongxia,
Yang Ping,
Xu Zhirong,
He Ting,
Lu Zhilin
Publication year - 2017
Publication title -
the journal of engineering
Language(s) - English
Resource type - Journals
ISSN - 2051-3305
DOI - 10.1049/joe.2017.0725
Subject(s) - demand response , electricity , computer science , electricity market , electric power system , reliability engineering , peak demand , database transaction , load management , stability (learning theory) , dynamic demand , power (physics) , engineering , electrical engineering , physics , quantum mechanics , machine learning , programming language
With the advancement of the electricity market reform process, the time scale of market transaction reduces, and the requirements of power systems have become more stringent. First, the rules and trends of deviation electric quantity assessment are expounded, and the demand response strategies are analysed, which include the autonomous power plant power allocation decision scheme, flexible load response analysis and energy storage regulation strategy to reduce punishment caused by the load forecasting error and to enhance the stability of the power system. An improved differential particle swarm optimisation algorithm is used to solve the demand‐side response strategy. The simulation results show that the demand response strategies of the autonomous power plant and flexible load with energy storage response can meet the demand of deviation electric quantity assessment, reduce the cost of power users, improve the real‐time balance of the power system and promote the stable development of the spot market.