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Risk evaluation of electric vehicle charging infrastructure public- private partnership projects in China using fuzzy TOPSIS

机译:基于模糊TOPSIS的中国电动汽车充电基础设施公私合作项目风险评估

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With increasing worldwide attention on clean energy and sustainability of environment development, electric vehicle (EV) projects have been growing in number and scale all over the world. However, increasing demand-supply imbalance in charging infrastructure becomes the major obstacle of Chinese EV development. Governments are applying Public-Private Partnership (PPP) mode in this field to effectively make use of solid capital and advanced technological capability of private sector to improve charging performance and service. To ensure project success, risk evaluation, which has remained nebulous, has become a crucial step. This paper aims to explore risk factors through questionnaire survey and calculate the overall risk levels of EV charging infrastructure PPP projects with an integrated approach with Fuzzy Order Preference by Similarity to Ideal Solution (Fuzzy TOPSIS). Results of risk factors identification consisted of project/technical, political/legal, economic and social/environmental risk categories and four risk factors were selected for specific concern of charging infrastructure in China: inadequate PPP project experience, high battery cost, long charging period and power price rise. Overall risk levels of three alternative projects were evaluated and ranked with proposed approach whose feasibility and effectiveness were verified through a comparative analysis and a sensitivity analysis. Moreover, awareness of existing risks, suggestions were provided for private sectors of EV charging infrastructure PPP project. The detailed implications and limitations were presented in the suggestions and the conclusions. (C) 2018 Elsevier Ltd. All rights reserved.
机译:随着全球对清洁能源和环境发展可持续性的关注日益增加,电动汽车(EV)项目在世界范围内的数量和规模都在不断增长。然而,充电基础设施供需失衡加剧成为中国电动汽车发展的主要障碍。各国政府正在这一领域采用公私合营(PPP)模式,以有效利用雄厚的资本和私营部门的先进技术能力来改善充电性能和服务。为了确保项目成功,仍然模糊的风险评估已成为至关重要的一步。本文旨在通过问卷调查来探索风险因素,并采用与理想解决方案相似的模糊顺序偏好综合方法(Fuzzy TOPSIS)来计算电动汽车充电基础设施PPP项目的总体风险水平。风险因素识别的结果包括项目/技术,政治/法律,经济和社会/环境风险类别,并针对中国充电基础设施的具体考虑选择了四个风险因素:PPP项目经验不足,电池成本高,充电时间长和电力价格上涨。对三个备选项目的总体风险水平进行了评估,并采用提议的方法进行了排名,其方法和可行性通过比较分析和敏感性分析得到了验证。此外,对于现有风险的认识,为电动汽车充电基础设施PPP项目的私营部门提供了建议。建议和结论中介绍了详细的含义和局限性。 (C)2018 Elsevier Ltd.保留所有权利。

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