| 基于回归分析的迎峰度夏用电量分析 |
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| 引用本文： | 陈雨泽,李磊,方学民,刘建,赵加奎,刘玉玺,左松林. 基于回归分析的迎峰度夏用电量分析[J]. 电信科学, 2019, 35(11): 125-131. DOI: 10.11959/j.issn.1000-0801.2019274 |
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| 作者姓名： | 陈雨泽 李磊 方学民 刘建 赵加奎 刘玉玺 左松林 |
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| 作者单位： | 国网信息通信产业集团有限公司,北京,100085;国家电网有限公司,北京,100031;国家电网有限公司大数据中心,北京,100031;国网安徽省电力有限公司,安徽合肥,340001 |
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| 摘 要： | 利用回归分析算法，提出了一种迎峰度夏期间最高气温与日用电量关系分析方法，首先利用皮尔森相关系数对度夏期间的最高气温和日用电量相关程度进行定量分析，然后利用回归分析算法建立最高气温和日用电量的拟合函数，并利用最小二乘法进行求解，得到最高气温和日用电量相关关系的定量分析结果。研究结果表明，提出的度夏期间用电量分析方法能够定量地给出气温变化导致的用电量变化情况，并能根据分析结果对未来几天的日用电量进行准确预测。
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| 关 键 词： | 用电量 迎峰度夏 皮尔森相关系数 回归分析 最小二乘法 |
An analysis method for electricity consumption in peak load period of summer based on regression analysis |
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| Yuze CHEN,Lei LI,Xuemin FANG,Jian LIU,Jiakui ZHAO,Yuxi LIU,Songlin ZUO. An analysis method for electricity consumption in peak load period of summer based on regression analysis[J]. Telecommunications Science, 2019, 35(11): 125-131. DOI: 10.11959/j.issn.1000-0801.2019274 |
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| Authors: | Yuze CHEN Lei LI Xuemin FANG Jian LIU Jiakui ZHAO Yuxi LIU Songlin ZUO |
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| Affiliation: | 1. State Grid Information ＆Telecommunication Group Co.,Ltd.,Beijing 100085,China;2. State Grid Corporation of China,Beijing 100031,China;3. State Grid Big Data Center,Beijing 100031,China;4. State Grid Anhui Electric Power Co.,Ltd.,Hefei 340001,China |
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| Abstract: | A method for analyzing the relationship between daily maximum temperature and electricity consumption during peak load period was proposed.Firstly,the relationship between maximum temperature and electricity consumption was quantified by Pearson correlation coefficient.Secondly,the functional relationship was established using regression and solved by least squares method.The quantified result of the relationship between maximum temperature and electricity consumption was then acquired.The empirical research shows the proposed method for electricity consumption analysis during peak load period of summer can quantify the variation of daily electricity consumption caused by temperature change and predict electricity consumption of the next few days according to the analysis result. |
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| Keywords: | electricity consumption peak load period of summer Pearson correlation coefficient regression analysis least squares |
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