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负荷预测在配网规划中的研究及应用
引用本文:李小伟,陈 楚. 负荷预测在配网规划中的研究及应用[J]. 中州煤炭, 2021, 0(3): 143-147. DOI: 10.19389/j.cnki.1003-0506.2021.03.027
作者姓名:李小伟  陈 楚
作者单位:(广西电网有限责任电网规划研究中心,广西 南宁 530000)
摘    要:为了在配网规划中预测未来需求量及用电量,从而决定电网的发电、输电、配电系统新增容量大小,以及采用的发电设备类型,保证配电网系统运行的安全稳定经济性,提出对配网规划中可以运用负荷预测这一思路.以电力负荷预测作为研究着手点,在分析电力消费现状基础上,运用回归分析法、单耗法、趋势拟合法,预测某地2020—2024年的电力消费...

关 键 词:负荷预测  配网规划  回归分析

 Research and application of load forecasting in distribution network planning
Li Xiaowei,Chen Chu.  Research and application of load forecasting in distribution network planning[J]. Zhongzhou Coal, 2021, 0(3): 143-147. DOI: 10.19389/j.cnki.1003-0506.2021.03.027
Authors:Li Xiaowei  Chen Chu
Affiliation:(Guangxi Power Grid Limited Liability Power Grid Planning Research Center,Nanning 530000,China)
Abstract:In order to predict the future demand and power consumption in the distribution network planning,so as to determine the new capacity of power generation,transmission and distribution system,as well as the type of power generation equipment used,and ensure the safe,stable and economic operation of the distribution network system,this paper put forward the idea that load forecasting can be used in the distribution network planning.Taking the power load forecasting as the research starting point,based on the analysis of the current situation of power consumption,this paper used regression analysis method,unit consumption method and trend fitting method to forecast the power consumption of a certain place from 2020 to 2024,and compared and analyzed the forecasting effect of different forecasting methods in the distribution network planning.It was found that these three methods are obviously different in data samples,applicable conditions and modeling ideas.It was concluded that in the process of planning the distribution network,it is necessary to combine the development of power consumption and load influencing factors,and select the appropriate load forecasting method,so as to truly improve the security and stability of the operation of the distribution system and obtain higher social and economic benefits.
Keywords:  load forecasting   distribution network planning   regression analysis
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