[Oral Presentation]Generation maintenance scheduling based on multi-objective particle swarm optimization considering carbon emissions

Generation maintenance scheduling based on multi-objective particle swarm optimization considering carbon emissions
ID:52 Submission ID:143 View Protection:ATTENDEE Updated Time:2021-12-03 10:32:42 Hits:492 Oral Presentation

Start Time:2021-12-16 09:45 (Asia/Shanghai)

Duration:15min

Session:[A] Renewable energy system » [A3] Session 13

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Abstract
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.
Keywords
carbon emissions,generation maintenance scheduling,multi-objective particle swarm optimization
Speaker
Hengyuan Guo
School of Artificial Intelligence and Automation, Huazhong University of Science and Technology

Submission Author
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
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