143 / 2021-10-28 10:55:26
Generation maintenance scheduling based on multi-objective particle swarm optimization considering carbon emissions
carbon emissions,generation maintenance scheduling,multi-objective particle swarm optimization
终稿
Hengyuan Guo / School of Artificial Intelligence and Automation, Huazhong University of Science and Technology
Shangyang He / China-EU Institute for Clean and Renewable Energy, Huazhong University of Science and Technology
Cheng Huang / Ltd. Research Institute;State Grid Jiangsu Electric Power Co.
Qian Zhou / State Grid Jiangsu Electric Power Company Limited Research Institute
Yong Zhao / School of Artificial Intelligence and Automation, Huazhong University of Science and Technology
With the development of society, the carbon emissions generated by the power system grow rapidly. Under this consideration, this paper presents a multi-objective generation maintenance scheduling (GMS) model considering carbon trading in a market environment. The model includes three types of objectives: system reliability, system total cost, and regional carbon emissions. In this paper, the relationships among these objectives are analyzed, in addition, the consequences of changes in the price of carbon trading are also described. Simulation results show that multi-objective particle swarm optimization (MOPSO) can solve the model well. The simulation results also show that the reliability objective conflicts with other objectives, and there is a positive correlation between the total cost and the carbon trading cost. The simulation also indicates that a moderate price for carbon trading is better than a high price or a low price.
重要日期
  • 会议日期

    07月11日

    2023

    08月18日

    2023

  • 11月10日 2021

    初稿截稿日期

  • 12月10日 2021

    注册截止日期

  • 12月11日 2021

    报告提交截止日期

主办单位
IEEE IAS
承办单位
IEEE IAS Student Chapter of Southwest Jiaotong University (SWJTU)
IEEE IAS Student Chapter of Huazhong University of Science and Technology (HUST)
IEEE PELS (Power Electronics Society) Student Chapter of HUST
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