LAPSE:2023.12753
Published Article

LAPSE:2023.12753
Is the Renewable Portfolio Standard in China Effective? Research on RPS Allocation Efficiency in Chinese Provinces Based on the Zero-Sum DEA Model
February 28, 2023
Abstract
As one of the countries with the most rapid development of new energy, China has been committed to exploring countermeasures to the challenges of new energy consumption. After more than ten years of consideration and consultation, the “renewable portfolio standard“(RPS) for “renewable energy power consumption responsibility weighting” has landed in China. However, in the official affirmation issued by the National Energy Administration, theoretical support for the basis of the initial quota allocation is still lacking. In this study, we examine the efficiency of the weight allocation scheme for renewable energy power consumption responsibilities, which was announced by the National Energy Administration in 2018 and which is based on the BCC-DEA efficiency model. The results indicate that most provinces have low allocation efficiency under this allocation scheme. Therefore, we propose an optimal allocation scheme for a renewable energy consumption quota, based on the ZSG-DEA model. With the achievement of its target, this study’s allocation scheme would ensure 100% efficiency in all provinces, improve provincial economic efficiency, and simultaneously bring economic growth. After analyzing the fairness before and after adjustment of the RPS, our findings suggest that the adjusted RPS allocation scheme can promote equity in per capita renewable electricity consumption.
As one of the countries with the most rapid development of new energy, China has been committed to exploring countermeasures to the challenges of new energy consumption. After more than ten years of consideration and consultation, the “renewable portfolio standard“(RPS) for “renewable energy power consumption responsibility weighting” has landed in China. However, in the official affirmation issued by the National Energy Administration, theoretical support for the basis of the initial quota allocation is still lacking. In this study, we examine the efficiency of the weight allocation scheme for renewable energy power consumption responsibilities, which was announced by the National Energy Administration in 2018 and which is based on the BCC-DEA efficiency model. The results indicate that most provinces have low allocation efficiency under this allocation scheme. Therefore, we propose an optimal allocation scheme for a renewable energy consumption quota, based on the ZSG-DEA model. With the achievement of its target, this study’s allocation scheme would ensure 100% efficiency in all provinces, improve provincial economic efficiency, and simultaneously bring economic growth. After analyzing the fairness before and after adjustment of the RPS, our findings suggest that the adjusted RPS allocation scheme can promote equity in per capita renewable electricity consumption.
Record ID
Keywords
China’s renewable energy consumption, renewable portfolio standards, zero-sum DEA model, ZSG-DEA model
Subject
Suggested Citation
Wang S, Zhao W, Fan S, Xue L, Huang Z, Liu Z. Is the Renewable Portfolio Standard in China Effective? Research on RPS Allocation Efficiency in Chinese Provinces Based on the Zero-Sum DEA Model. (2023). LAPSE:2023.12753
Author Affiliations
Wang S: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China [ORCID]
Zhao W: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Fan S: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Xue L: State Grid Shanxi Economic Research Institute, Taiyuan 030021, China
Huang Z: Shanghai Envision Digital Technology Co., Ltd., Shanghai 200011, China
Liu Z: Beijing Bojin Hengxin Technology Consulting Company, Beijing 100080, China
Zhao W: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Fan S: College of Economics and Management, Shanghai University of Electric Power, Shanghai 200090, China
Xue L: State Grid Shanxi Economic Research Institute, Taiyuan 030021, China
Huang Z: Shanghai Envision Digital Technology Co., Ltd., Shanghai 200011, China
Liu Z: Beijing Bojin Hengxin Technology Consulting Company, Beijing 100080, China
Journal Name
Energies
Volume
15
Issue
11
First Page
3949
Year
2022
Publication Date
2022-05-27
ISSN
1996-1073
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PII: en15113949, Publication Type: Journal Article
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LAPSE:2023.12753
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https://doi.org/10.3390/en15113949
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Feb 28, 2023
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