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配网用户用电分析预测模型的参数设置管理研究 被引量:2

Research on Parameters Setting and Management of Distribution Network User Electricity Consumption Analyzing and Forecasting Model
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摘要 通过用电市场研究分析,细分用电行业市场,有利于建立常态市场下配网用户用电分析预测模型,讨论了该模型的参数设置管理,包括驱动因素管理和大户调查管理。重点讨论了参数设置管理,包括驱动因素管理和细分行业管理。针对前者,结合东莞用电量,实例分析了驱动因素数据预测的方法,包括产量预测法、出口产值预测法、价格指数预测法、温度预测法、GDP预测法等;针对后者,对行业与驱动因素关系进行了定义,就行业及驱动因素历史数据平滑系数的设置,提出了利用回归分析的方法,设置相关的平滑系数,并给出了回归分析结果,并获取了标准差。通过对模型参数设置管理的探讨,为建立配网用户用电分析预测模型奠定重要基础。 Based on electricity market research and analysis, as well as detailed classification of electricity industrymarket, it’s beneficial to build distribution network user electricity analysis and forecasting model under normal market. Adiscussion was made on parameters setting and management of the model, including driving factors management and big usersinvestigation management, especially the former was emphatically discussed, which included the driving factors managementand segmentation industries management, aimed at the former, combined with practical example analysis of electricityconsumption of Dongguan city, the driving factors forecasting methods were studied, including the production predictionmethod, the output value prediction method, price index prediction method, temperature prediction method, and GDP predictionmethod. Aimed at big users management, a regression analysis method was proposed to set the corresponding smoothingcoefficients, and the regression analysis results and standard deviations were given. Based on discussion of model parameterssetting and management, it laid a foundation for distribution network user electricity consumption analysis and forecastingmodel.
作者 吕润婵 LV Run-chan(Dongguan Power Supply Bureau of Guangdong Power Grid Co., Ltd., Dongguan 523000, China)
出处 《新型工业化》 2016年第6期39-49,共11页 The Journal of New Industrialization
基金 中国南网电网科技项目资助(GDKJ00000052)
关键词 用电分析预测 参数设置管理 驱动因素管理 细分行业管理 平滑系数 回归分析 Electricity consumption analysis and forecasting Parameters setting and management Driving factors management Segmentation industries management Smoothing coefficient regression analysis
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