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重庆地区电力负荷特性及其影响因素分析
引用本文:雷绍兰,古亮,杨佳,刘欣宇. 重庆地区电力负荷特性及其影响因素分析[J]. 中国电力, 2014, 47(12): 61-65. DOI: 10.11930/j.issn.1004-9649.2014.12.61.4
作者姓名:雷绍兰  古亮  杨佳  刘欣宇
作者单位:1. 重庆理工大学 电子信息学院,重庆 400054;2. 重庆市电力公司,重庆 400014
基金项目:国家青年科学基金资助项目(51107155)
摘    要:研究电力负荷变化特性和规律对提高短期负荷预测精度具有重要意义。根据重庆地区近年来收集的历史负荷数据和气象数据等相关信息,分析了年最大和最小负荷及典型日负荷曲线的变化规律,研究了该地区的负荷特性与主要影响因素之间的相互关系,并针对重庆地域特点,分析了各主要影响因素对该地区负荷的影响程度和主要影响时段。研究结果表明,目前温度、降雨量和节假日对重庆地区电力负荷的影响较大,可为研究重庆地区电力短期负荷预测方法和分析未来智能电网的负荷特性提供理论依据。

关 键 词:电力负荷  气象因子  相关性  影响因素  负荷特性  
收稿时间:2014-09-13

Analysis of Electric Power Load Characteristics and Its Influencing Factors in Chongqing Region
LEI Shao-lan,GU Liang,YANG Jia,LIU Xin-yu. Analysis of Electric Power Load Characteristics and Its Influencing Factors in Chongqing Region[J]. Electric Power, 2014, 47(12): 61-65. DOI: 10.11930/j.issn.1004-9649.2014.12.61.4
Authors:LEI Shao-lan  GU Liang  YANG Jia  LIU Xin-yu
Affiliation:1. School of Electronic Information and Automation, Chongqing University of Technology, Chongqing 400054, China;2. Chongqing Electric Power Corp., Chongqing 400014, China
Abstract:It is very important to study the load variation characteristics for improving the short-term load forecasting accuracy. The variation characteristics of the annual maximum load, annual minimum load and typical daily load is analyzed in this paper based on the recent historical load data and meteorological data of Chongqing region. Besides, the interrelationship between the load characteristics and the major influencing factors is studied, and the influencing extent of the major factors on the region’s load and the main influencing time period are analyzed according to Chongqing’s geographic characteristics. The results show that the temperature, rainfall, holidays and festivals have a significant influence on the Chongqing region’s power load at present, which can provide a theoretical basis for studying the short-term load forecasting method and analyzing the smart grid load characteristics.
Keywords:electric power load  meteorological factor  correlation  influencing factor  load characteristics  
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