Electric Power ›› 2022, Vol. 55 ›› Issue (1): 151-158.DOI: 10.11930/j.issn.1004-9649.202009107

Previous Articles     Next Articles

Modeling and Analysis of Daily Generation Schedule Considering the Coexistence of Planned Electricity and Market Trading Electricity

ZHANG Shuying1, LI Gang2, TENG Xiaobi2, CHENG Jifeng1, YAN Zheng1, WANG Han1   

  1. 1. Key Laboratory of Control of Power Transmission and Conversion, Ministry of Education (Shanghai Jiao Tong University), Shanghai 200240, China;
    2. East China Branch of State Grid Corporation of China, Shanghai 200120, China
  • Received:2020-09-27 Revised:2021-08-26 Online:2022-01-28 Published:2022-01-20
  • Supported by:
    This work is supported by Science and Technology Project of SGCC (Research on the Reconstruction of East China's Dispatching Business and Regional Electricity Auxiliary Service Mechanism Under the Electricity Spot Market, No. SGTYHT/19-JS-214)

Abstract: With the continuous promotion of China's electricity market-oriented reform, some provinces and cities will gradually introduce market-oriented trading means on the basis of traditional generation schedule. In this context, how to establish the daily generation schedule model considering planned and trading electricity is an urgent problem to be solved. In this paper, a model of daily generation schedule that combines planned electricity decomposition and Nash equilibrium of market trading electricity is established, in which the existing mode of generation schedule is taken into account. By means of solving the model, the daily generation plan was evaluated in two aspects of economy and security, by studying the impact of different market openness. An example simulation of a provincial power grid in East China is given to analyze the impacts of different market trading electricity proportion on the generation cost and power shortage expectation of the whole system, and verify rationality and effectiveness of the proposed model.

Key words: electricity market, generation plan, Nash equilibrium, particle swarm optimization algorithm