本文選題：集中型充電站 + 用戶滿意度��； 參考：《高電壓技術(shù)》2017年04期

【摘要】：考慮到充電站投資主體和充電用戶兩種不同角色所追求的利益互異會影響充電站規(guī)劃決策,發(fā)展了一種兼顧投資主體投資成本和充電用戶滿意度的集中型充電站雙層優(yōu)化布局模型。根據(jù)各類電動汽車(EVs)的行為特性建立了電動汽車充電功率需求模型。以企業(yè)投資成本和用戶滿意度分別作為雙層規(guī)劃模型的上層和下層目標(biāo)函數(shù),并考慮企業(yè)投資預(yù)算約束、電網(wǎng)約束、充電站容量約束和充電用戶需求約束,綜合反映了不同角色間的耦合決策作用。雙層規(guī)劃問題屬于強(qiáng)NP-hard問題,采用量子遺傳算法求解上層規(guī)劃模型,采用粒子群算法求解下層規(guī)劃模型,并輸出最終充電站布局方案。結(jié)果表明,綜合考慮投資成本和用戶滿意度的集中型充電站方案能合理兼顧投資主體和用戶的各自利益,實(shí)現(xiàn)投資成本和用戶滿意度的有效折衷。
[Abstract]:Considering that the different interests pursued by the two different roles of charging station investors and charging users may affect the planning decisions of charging stations, In this paper, a double layer optimal layout model for charging stations is developed, which takes into account the investment cost of the investors and the satisfaction of charging users. According to the behavior characteristics of various electric vehicles (EVs), a charging power demand model for electric vehicles is established. The enterprise investment cost and customer satisfaction are taken as the upper and lower level objective functions of the bilevel programming model respectively, and the investment budget constraints, power network constraints, charging capacity constraints and charging user demand constraints are considered. It reflects the coupling decision function between different roles. The bilevel programming problem is a strong NP-hard problem. Quantum genetic algorithm (QGA) is used to solve the upper programming model and particle swarm optimization (PSO) is used to solve the lower programming model, and the final charging station layout scheme is outputted. The results show that the scheme of integrated investment cost and customer satisfaction can give consideration to the interests of investors and users and realize an effective compromise between investment cost and customer satisfaction.
【作者單位】： 四川大學(xué)電氣信息學(xué)院;國網(wǎng)四川省電力公司電力科學(xué)研究院;
【基金】：國家自然科學(xué)基金(51377111)~~
【分類號】：U491.8
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本文編號：2110061