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基于GMC(1,N)的多因素负荷预测模型及其应用 被引量:2

Multi-element Load Forecasting Model Based on GMC(1,N) and Its Application
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摘要 电力负荷受多种因素的影响,不能把负荷数据当成"纯粹"的数据看待,重视负荷成因分析是进行准确预测的前提。根据灰色预测的基本原理,通过增加影响负荷的白信息量来降低预测系统的灰度,以传统灰色GM(1,N)模型为基础,应用多变量灰色数列卷积预测模型--GMC(1,N)模型,该模型克服了传统GM(1,N)模型的不足,扩宽了GM(1,N)模型的应用范围。并将GMC(1,2)、GMC(1,3)模型应用于实例,结果证明该方法预测准确,并且由于考虑实际因素的影响,可靠性高,可作为中长期负荷预测工具之一。 The load of power system is affected by many different factors.It cannot be handled as simple data.It is necessary to improve the prediction accuracy by analyzing the composition of power load.According to the basic principle of gray prediction,the gray degree of the system to be predicted can become lower as the white information associated with power load increases.A multi-variant gray model with convolution named GMC(1,N) for prediction is proposed based on traditional gray model GM(1,N).The GMC(1,N) has...
出处 《四川电力技术》 2008年第6期73-76,共4页 Sichuan Electric Power Technology
关键词 电力系统负荷预测 灰色预测 预测模型 卷积 load forecasting of power system grey forecasting forecasting model convolution
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