基于拟合优度赋权的农网用电需求组合预测

doi:10.3969/j.issn.1000-7229.2015.08.009

电力建设 ›› 2015, Vol. 36 ›› Issue (8): 55-60.doi: 10.3969/j.issn.1000-7229.2015.08.009

基于拟合优度赋权的农网用电需求组合预测

刘思1，白桦2，张凯2，叶承晋2，黄民翔1

1.浙江大学电气工程学院，杭州市 310027； 2.国网浙江省电力公司经济技术研究院，杭州市 310008

出版日期:2015-08-01
作者简介:刘思（1991），女，硕士研究生，主要研究方向为电力系统需求侧管理、电力系统规划与可靠性；白桦（1979），男，副高级工程师，主要从事电力系统配电网规划、项目评审工作；张凯（1987），男，工程师，主要从事电力系统配电网规划、可研项目评审工作；叶承晋（1987），男，工程师，主要从事电力系统配电网规划、电力系统优化相关工作；黄民翔（1955），男，教授，主要研究方向为电力系统规划与电力市场。

Power Demand Combination Forecasting of Rural Power Network Based on Goodness of Fit Empowerment

LIU Si1, BAI Hua2, ZHANG Kai2, YE Chengjin2, HUANG Minxiang1

1. College of Electrical Engineering, Zhejiang University, Hangzhou 310027, China； 2. Economic Research Institute of State Grid Zhejiang Electric Power Company, Hangzhou 310008, China

Online:2015-08-01

摘要/Abstract

摘要：

在我国新型城镇化和美丽乡村宏观政策的推动下，城乡一体化进程加快，带动农网用电需求快速增长。分析新型城镇化和美丽乡村背景下的农网用电需求，对建立和完善乡镇电网发展模式和建设标准具有重要现实意义。结合新型城镇化和美丽乡村背景下的农网用电需求特点，建立了城镇用电需求评估指标体系，提出一种基于全样本空间的类比预测法，将用电需求预测从单一维度扩展到多维空间，适用于目前城镇化过程中电力数据和经济社会发展信息交汇的大数据环境。在此基础上，综合回归分析法、灰色模型、人均用电量法等3种经典预测方法，设计了基于拟合优度赋权的组合预测算法，实现了权重的自动优化调整，算例结果表明组合预测算法提高了预测的精度和可靠性。

关键词: 用电需求预测, 全样本空间, 组合预测, 拟合优度, 新型城镇化

Abstract:

With the promotion of the new urbanization and beautiful countryside macro policy in China, the process of the urban-rural integration accelerates, which drives the fast increase in the demand of the rural power network. In the background of the new urbanization and beautiful countryside, the analysis of the demand of the rural power network has the important practical significance to the establishment and improvement of the development model and construction standard of rural power network. Combining the power demand characteristics of rural power network in the background of the new urbanization and beautiful countryside, the power demand evaluation indexes for town are established and the analogy forecasting method is proposed based on full sample space, which could extend the load forecasting from a single dimension to hyperspace. It is applicable to the big data environment where the power data intersected the economic and social development in the process of urbanization. On this basis, this paper synthesizes the three classic forecasting methods, including the regression analysis method, the grey model and the per capita consumption method, and proposes a combination forecasting method based on the goodness of fit empowerment, which could realize the automatic optimization adjustment of weight. The numerical example results show that the combination forecasting method can improve the accuracy and reliability of the forecasting results.

Key words: power demand forecasting, full sample space, combination forecasting, goodness of fit, new urbanization

中图分类号:

TM 715
TU 47

刘思，白桦，张凯，叶承晋，黄民翔. 基于拟合优度赋权的农网用电需求组合预测[J]. 电力建设, 2015, 36(8): 55-60.

LIU Si, BAI Hua, ZHANG Kai, YE Chengjin, HUANG Minxiang. Power Demand Combination Forecasting of Rural Power Network Based on Goodness of Fit Empowerment[J]. ELECTRIC POWER CONSTRUCTION, 2015, 36(8): 55-60.

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基于拟合优度赋权的农网用电需求组合预测

Power Demand Combination Forecasting of Rural Power Network Based on Goodness of Fit Empowerment

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