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Province-level performance assessment of China's two-stage power supply system

Published: 29 May 2024 Publication History

Abstract

As China's economy develops and social demand for electricity maintains rigid growth, carbon dioxide emissions from China's power supply system (PSS) are increasing. How to reduce carbon emissions while ensuring sufficient power supply is an issue that needs to be considered in China's power supply system. Therefore, this paper constructs a two-stage leader-follower directional distance function (DDF) to assess the performance of China's power supply system through data from 30 provinces in China from 2015 to 2018. The empirical results show that the performance of the power generation stage performs significantly better than the power sales stage. The overall average efficiency is higher in the western and eastern regions of China than in the central region.

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  1. Province-level performance assessment of China's two-stage power supply system

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    BDEIM '23: Proceedings of the 2023 4th International Conference on Big Data Economy and Information Management
    December 2023
    917 pages
    ISBN:9798400716669
    DOI:10.1145/3659211
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 29 May 2024

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    Funding Sources

    • Shenzhen University Humanities and Social Sciences High-level Innovation Team Project for Leading Scholars
    • Key Project of National Social Science Foundation of China
    • Shenzhen Science and Technology Program

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    BDEIM 2023

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