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Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm

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  • Qiao, Baihao
  • Liu, Jing

Abstract

Electric vehicles (EVs) are currently the most popular green transportation. Wind power has received widespread attention as a kind of renewable energy source. Their rapid development has brought new challenges for the power grid. However, the technology of vehicle to grid (V2G) can realize the peak shaving of the power grid, which is considered to be an effective method to promote the integration of EVs and wind power. Therefore, in this paper, a novel integrated framework of EVs and wind farms (WEV) is proposed to use the EVs charging and discharging to smooth the wind power penalty cost that caused by overestimated and underestimated of available wind power. While a new multi-objective dynamic economic emission dispatching model based on the WEV system (WE_DEED) is developed to consider both emission and total cost objectives. In order to solve the complex constrained WE_DEED problem, we propose a multi-objective differential evolution algorithm with the self-adaptive parameter operator and local search operator based on non-dominant sorting (SaMODE_LS). Moreover, an effective constraint handling method is applied to deal with the constraints in WE_DEED problems. Different test systems based on 10-unit are given to demonstrate the reasonability and efficiency of the proposed model and method.

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  • Qiao, Baihao & Liu, Jing, 2020. "Multi-objective dynamic economic emission dispatch based on electric vehicles and wind power integrated system using differential evolution algorithm," Renewable Energy, Elsevier, vol. 154(C), pages 316-336.
    • Handle: RePEc:eee:renene:v:154:y:2020:i:c:p:316-336
    DOI: 10.1016/j.renene.2020.03.012
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    References listed on IDEAS

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