| 基于统计理论的负荷特性分析及其预测 |
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| 引用本文： | 陈墨,聂宗铭,夏旭.基于统计理论的负荷特性分析及其预测[J].东北电力学院学报,2011(2):55-61. |
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| 作者姓名： | 陈墨 聂宗铭 夏旭 |
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| 作者单位： | 满洲里达赉湖热电有限公司;贵州电网公司水城供电局;龙嘉机场; |
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| 摘 要： | 电力负荷受气象因素影响越来越大,如何准确确定气象因素是负荷预测研究的重要课题.首先采用统计学方法对影响负荷的气象因素进行分析,找到影响负荷的核心气象因索,再利用GRNN回归神经网络进行预测.经实际系统检验,证明该方法克服了传统气象负荷预测中的主观性,将气象影响因素过程量化,提高了预测结果的精度,是一种适用性很强的方法.
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| 关 键 词： | 电力系统 负荷预测 气象因素 神经网络 |
Short-term electric load forecasting based on statistics theoretical was employed to power load |
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| CHEN Mo,NIE Zong-ming,XIA Xu.Short-term electric load forecasting based on statistics theoretical was employed to power load[J].Journal of Northeast China Institute of Electric Power Engineering,2011(2):55-61. |
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| Authors: | CHEN Mo NIE Zong-ming XIA Xu |
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| Affiliation: | CHEN Mo1,NIE Zong-ming2,XIA Xu3(1.Manzhouli Dalaihu Thermal Power Company Ltd,Manzhouli Neimenggu 021406,2.Guizhou Stata Grid Coporation of China,Chuicheng Power Supply Bureau,Chuicheng Guizhou 553001,3.Changchun Longjia Airport,Changchun 131011) |
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| Abstract: | Weather condition has an increasing influence upon the power load.How to forecast the weather load is a important research subject.In this paper,first statistics theoretical was employed to process attribute reduction on weather factors that will influence power load;this procedure can find the essential factors in power load.Then these essential factors were used as coordinates to find the nearest historical data as input for GRNN neural networks model.The method can avoid the subjectivity of traditional f... |
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| Keywords: | Power system Load forecasting Weather factor Neural networks |
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