基于地理探测器的广州市分行业月度用电特点及优化管理

doi:10.11930/j.issn.1004-9649.202004118

中国电力 ›› 2021, Vol. 54 ›› Issue (9): 125-134.DOI: 10.11930/j.issn.1004-9649.202004118

基于地理探测器的广州市分行业月度用电特点及优化管理

张云涛^1,2,3, 蔡国田^1,2,3, 柯尚军^1,2,4, 王文秀^1,2

1. 中国科学院广州能源研究所，广东广州 510640;
2. 中国科学院可再生能源重点实验室，广东广州 510640;
3. 中国科学院大学，北京 100049;
4. 中国科学技术大学纳米科学技术学院，江苏苏州 215123

收稿日期:2020-04-15 修回日期:2020-10-22 发布日期:2021-09-14
作者简介:张云涛(1996-),男,硕士研究生,从事能源战略研究,E-mail:380945650@qq.com;蔡国田(1975-),男,通信作者,博士,研究员,从事能源战略、经济地理等研究,E-mail:caigt@ms.giec.ac.cn
基金资助:
广东省软科学研究计划项目(2016A080803002)；广东省科技计划资助项目(2018A050501011)；广州市基础与应用基础研究项目(202002030189)

Monthly Electricity Consumption Characteristics of Industries in Guangzhou and Optimized Electricity Management Based on Geographical Detector

ZHANG Yuntao^1,2,3, CAI Guotian^1,2,3, KE Shangjun^1,2,4, WANG Wenxiu^1,2

1. Guangzhou Institute of Energy Conversion, CAS, Guangzhou 510640, China;
2. Key Laboratory of Renewable Energy, CAS, Guangzhou 510640, China;
3. University of Chinese Academy of Sciences, Beijing 100049, China;
4. Nano Science and Technology Institute, University of Science and Technology of China, Suzhou 215123, China

Received:2020-04-15 Revised:2020-10-22 Published:2021-09-14
Supported by:
This work is supported by Soft Science Research Program of Guangdong Province (No. 2016A080803002), Science and Technology Project of Guangdong Province (No.2018A050501011), Basic and Applied Basic Research Project of Guangzhou (No.202002030189)

摘要/Abstract

摘要： 为将广州市电力需求侧管理落实到具体行业，使用地理探测器、用电互补性模型分析2013—2017年共60个月各行业用电特点，在此基础上，通过情景分析方法，从行业、时间角度探索行业用电优化管理路径。基于广州市分行业月度用电特点，抓住行业用电量风向标子行业，利用存在可相互抵消用电波动的用电组合，研究发现：在2017年广州市用电量水平下优化行业用电结构和优化用电时间管理总计可减小约2.25亿kW·h的全社会用电月度峰谷差。未来可通过分行业月度用电预测、结合用电互补性分析测算行业用电调度潜力，为电力需求侧管理水平提高提供数据支撑。

关键词: 行业月度用电量, 地理探测器, 用电互补性, 情景分析, 优化管理

Abstract: To implement demand-side management (DSM) to specific industries, this paper analyzed electricity consumption characteristics of each industry within 60 months from 2013 to 2017, depending on the geographical detector and the electricity consumption complementarity model. On this basis, it explored the optimal management path of industry electricity consumption from the perspective of industry and time through scenario analysis. In light of the monthly electricity consumption characteristics of different industries in Guangzhou, the main driving sub-industries for electricity consumption in the industry were identified, and the electricity consumption combinations that can offset the fluctuation in electricity consumption were employed. The research finds that optimizing the industrial electricity consumption structure and upgrading the consumption time management considering the electricity consumption level of Guangzhou in 2017 can reduce the monthly peak–valley difference of Guangzhou electricity consumption by about 225 million kW·h. In the future, the monthly electricity consumption forecast of the industry, combined with the analysis of electricity complementarity, can be used to calculate the industry’s electricity dispatching potential, so as to provide data support for the improvement in demand-side management of electricity.

Key words: monthly electricity consumption of industry, geographical detector, electricity complementarity, scenario analysis, optimal management

张云涛, 蔡国田, 柯尚军, 王文秀. 基于地理探测器的广州市分行业月度用电特点及优化管理[J]. 中国电力, 2021, 54(9): 125-134.

ZHANG Yuntao, CAI Guotian, KE Shangjun, WANG Wenxiu. Monthly Electricity Consumption Characteristics of Industries in Guangzhou and Optimized Electricity Management Based on Geographical Detector[J]. Electric Power, 2021, 54(9): 125-134.

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基于地理探测器的广州市分行业月度用电特点及优化管理

Monthly Electricity Consumption Characteristics of Industries in Guangzhou and Optimized Electricity Management Based on Geographical Detector

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基于地理探测器的广州市分行业月度用电特点及优化管理

Monthly Electricity Consumption Characteristics of Industries in Guangzhou and Optimized Electricity Management Based on Geographical Detector

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