Low Carbon Economic Dispatch of Power Systems with Wind Power for Electric Vehicle Carbon Quotas

被引:0
|
作者
Gao Yang [1 ]
Huang Fei [2 ]
Huang Zhengwen [3 ]
Li Guoquan [4 ]
Jia Jinshuo [4 ]
机构
[1] Chongqing Univ Posts & Telecommun, Sch Commun & Informat Engn, Chongqing, Peoples R China
[2] Inst Grid Chongqing Elect Power Co, Elect Power Sci Res, Chongqing, Peoples R China
[3] Brunel Univ, Dept Elect & Elect Engn, London, England
[4] Chongqing Univ Posts & Telecommun, Grp Artificial Intelligence & Syst Optimizat, Chongqing, Peoples R China
关键词
Carbon emissions; Electric vehicle; Clean energy; Economic scheduling;
D O I
10.1109/ACFPE59335.2023.10455123
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
With The rapid advancement of electric vehicles (EVs) and renewable energy technologies has opened up new possibilities for their integration into low-carbon power systems. Considering EVs as a flexible dispatch resource and incorporating them into the economic dispatch of power systems containing scenic power farms is crucial for effectively meeting low-carbon and carbon-reduction environmental requirements. This paper aims to construct an optimized dispatch model that minimizes both generation costs and carbon emissions of the power system. To address this challenge, we propose a genetic algorithm based on irregular coding as a solution to the dispatch model. Through extensive simulations, we validate that the proposed method significantly reduces computational resource requirements while achieving optimal scheduling of power generation units in the system. The method offers a cost-effective solution with low computational complexity while ensuring compliance with power constraints for scenic power generation. As a result, the approach presented in this paper holds great significance in progressively optimizing the co-dispatch of electric vehicles and renewable energy.
引用
收藏
页码:356 / 361
页数:6
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