Suzhou Electric Appliance Research Institute
期刊号: CN32-1800/TM| ISSN1007-3175

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兼顾供电量组分特性的最优GM(1,N )季度电量预测方法

来源:电工电气发布时间:2018-01-22 12:22 浏览次数:718
兼顾供电量组分特性的最优GM(1,N )季度电量预测方法
 
李京平1,陈丹伶2,曾繁华1,王鑫2,方嵩1
(1 广东电网有限责任公司中山供电局,广东 中山 528400;2 广州市奔流电力科技有限公司,广东 广州 510640)
 
    摘 要:提出考虑供电量组分多层级划分及外部因素影响,利用关联度寻优方法构造最优GM(1,N )电量预测模型。根据供电地区的行业用电分类,对总供电量的组分进行分层级划分和重要性分析;计算各重要组分及外部影响因素与供电量的关联度,并依据关联度大小对各影响因素进行排序,再通过建立不同N下的GM(1,N ) 模型,根据预测精度确定最优GM(1,N ) 模型。采用该模型对广东电网中山供电局的供电量数据进行预测分析,证明了该模型的预测结果具有较高的准确性。
    关键词:季度电量预测;GM(1,N ) 模型;行业用电分类;外部影响因素
    中图分类号:TM715     文献标识码:A     文章编号:1007-3175(2018)01-0027-05
 
Optimal GM (1, N) Quarter Electric Quantity Forecasting Method Considering Characteristics of Power Supply Components
 
LI Jing-ping1, CHEN Dan-ling2, ZENG Fan-hua1, WANG Xin2, FANG Song1
(1 Zhongshan Power Supply Bureau, Guangdong Power Grid Co., Ltd, Zhongshan 528400, China;
2 Guangzhou Power Electrical Engineering Technology Co., Ltd, Guangzhou 510640, China)
 
    Abstract: This paper proposed to use the correlation optimization method to construct the optimal GM (1, N) electric quantity prediction model considering the power supply components multilevel division and external influencing factors. According to the industry power utilization classification of power supply area, this paper carried out the power supply components multilevel division, analyzed the importance of the power supply components and calculated the correlation between each important component, together with external influencing factors and the power supply components. Each influencing factor was sorted based on the correlation and the GM (1, N) model of different N was established to determine the optimal one according to the prediction accuracy. The actual power supply data of Zhongshan power supply bureau of Guangdong power grid verifies the high accuracy of this model’s forecasting algorithm.
    Key words: quarter power supply forecasting; GM (1, N) model; industry power utilization classification; external influencing factor
 
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