Strategies of electricity enterprises and urban parks cooperatively investing in electric vehicle charging stations

IF 6.7 1区 工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS
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Abstract

Cities are increasingly pursuing sustainable development. To this end, we constructed two game models of cooperation between the electricity enterprise and the urban park manager to invest in charging stations (CSs) of energy vehicles (EVs). Model A involves revenue sharing between these entities, while Model B assumes that the electricity enterprise pays site leasing fees to the urban park manager. The CS investment capacity constraint is also considered. Based on the equilibrium solution of the models, we draw the following conclusions. Firstly, when the CS investment capacity constraint is small, the CS investment amount is equal under both models, while the leasing model provides a higher charging price and lower electricity demand for CS. Secondly, when the CS investment capacity constraint is moderate, the CS investment amount under the leasing model and the charging price are higher. The electricity demand for CS is mainly affected by the revenue sharing ratio. Thirdly, when the CS investment capacity constraint is high, the CS investment amount is affected by the finding cost of CS and the charging price changes accordingly with the electricity demand for CS. Finally, a decrease in the finding cost of CS does not necessarily lead to greater investment in CSs.

电力企业与城市公园合作投资电动汽车充电站的策略
城市越来越追求可持续发展。为此,我们构建了电力企业与城市公园管理者在投资能源汽车(EV)充电站(CS)方面合作的两个博弈模型。模型 A 涉及这两个实体之间的收入共享,而模型 B 则假定电力企业向城市公园管理者支付场地租赁费。同时还考虑了 CS 投资能力约束。根据模型的均衡解,我们得出以下结论。首先,当 CS 投资能力约束较小时,两种模式下的 CS 投资额相等,而租赁模式提供了更高的充电价格和更低的 CS 用电需求。其次,当希尔思投资能力限制适中时,租赁模式下的希尔思投资额和充电价格都较高。CS 用电需求主要受收入分成比例的影响。第三,当希尔思投资能力约束较高时,希尔思投资额会受到希尔思寻找成本的影响,充电价格也会随着希尔思用电需求的变化而相应变化。最后,CS 寻找成本的降低并不一定导致 CS 投资的增加。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Computers & Industrial Engineering
Computers & Industrial Engineering 工程技术-工程:工业
CiteScore
12.70
自引率
12.70%
发文量
794
审稿时长
10.6 months
期刊介绍: Computers & Industrial Engineering (CAIE) is dedicated to researchers, educators, and practitioners in industrial engineering and related fields. Pioneering the integration of computers in research, education, and practice, industrial engineering has evolved to make computers and electronic communication integral to its domain. CAIE publishes original contributions focusing on the development of novel computerized methodologies to address industrial engineering problems. It also highlights the applications of these methodologies to issues within the broader industrial engineering and associated communities. The journal actively encourages submissions that push the boundaries of fundamental theories and concepts in industrial engineering techniques.
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