Risk Evaluation of Electric Power Grid Investment in China Employing a Hybrid Novel MCDM Method

Yana Duan, Yang Sun, Yu Zhang, Xiaoqi Fan, Qinghuan Dong and Sen Guo
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Yana Duan: National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China
Yang Sun: National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China
Yu Zhang: National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China
Xiaoqi Fan: National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China
Qinghuan Dong: National Electric Power Grid Inner Mongolia Eastern Electric Power Co., Ltd., Economic and Technological Research Institute, Hohhot 010000, China
Sen Guo: School of Economics and Management, North China Electric Power University, Beijing 102206, China

Mathematics, 2021, vol. 9, issue 5, 1-22

Abstract: Socio-economic development is undergoing changes in China, such as the recently proposed carbon peak and carbon neutral targets, new infrastructure development strategy and the Coronavirus disease 2019 (COVID-19) pandemic. Meanwhile, the new-round marketization reform of the electricity industry has been ongoing in China since 2015. Therefore, it is urgent to evaluate the risk of electric power grid investment in China under new socio-economic development situation, which can help the investors manage risk and reduce risk loss. In this paper, a hybrid novel multi-criteria decision making (MCDM) method combining the latest group MCDM method, namely, Bayesian best–worst method (BBWM) and improved matter-element extension model (IMEEM) is proposed for risk evaluation of electric power grid investment in China under new socio-economic development situation. The BBWM is used for the weights’ determination of electric power grid investment risk criteria, and the IMEEM is employed to rank risk grade of electric power grid investment. The risk evaluation index system of electric power grid investment is built, including economic, social, environmental, technical and marketable risks. The risk of electric power grid investment under new socio-economic development situation in Inner Mongolia Autonomous Region of China is empirically evaluated by using the proposed MCDM method, and the results indicate that it belongs to “Medium” grade, but closer to “High” grade. The main contributions of this paper include: (1) it proposes a hybrid novel MCDM method combining the BBWM and IMEEM for risk evaluation of electric power grid investment; and (2) it provides a new view for risk evaluation of electric power grid investment including economic, social, environmental, technical and marketable risks. The proposed hybrid novel MCDM method for the risk evaluation of electric power grid investment is effective and practical.

Keywords: electric power grid investment (EPGI); risk evaluation (RE); bayesian best–worst method (BBWM); improved matter-element extension model (IMEEM); hybrid MCDM method (HMCDM) (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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