| 531 | 14 | 300 |
| 下载次数 | 被引频次 | 阅读次数 |
根据配电网网格化规划的要求,在电网规划供电单元、供电网格、供电区域划分的基础上,自下而上给出了3个层级的空间负荷预测方法。在供电单元层级,针对负荷密度法过程中负荷密度指标的选取,提出用S型曲线模型来确定过渡年负荷密度指标的方法,并给出了供电单元内同时率的计算方法,以此来确定供电单元负荷;对于供电网格层级,考虑供电单元间的同时率,给出了供电网格的负荷预测方法;由于供电网格为面积较大的综合型区域,它们之间的同时率接近于1,因此供电区域负荷为供电网格负荷直接相加。各个层级的负荷预测方法较传统的总量负荷预测更为精细化,为网格化规划中的高中压电网规划奠定了基础。
Abstract：According to the grid planning requirements of the distribution network, the load forecasting methods in the power supply unit, the power supply grid and the power supply area were presented. At the level of power supply unit, aiming at the selection of the transition year load density index in the process of the load density method, an S-curve model was proposed, and the calculation method of the load simultaneity factor in the power supply unit was given to determine power supply unit load. At the power supply grid level, considering the load simultaneity factor between power supply units, a load forecasting method for the power supply grid was given. Since the power supply grid was a comprehensive area in a large area, and the load simultaneity factor among them was close to 1, the load of the power grid could be directly added to get the power supply grid load. The load forecasting method at each level was more refined than the traditional total load forecasting method, which laid a solid foundation for the grid planning of high and middle voltage networks.
[1] 陈志强.自然区域电网负荷预测及规划的研究[D].保定:华北电力大学(河北),2009.CHEN Z Q.Research on power load forecasting and transmission network planning of natural areas[D].Baoding:North China Electric Power University,2009.
[2] 邵恒,冯兴乐,包芬.基于深度学习的文本相似度计算[J].郑州大学学报(理学版),2020,52(1):66-71,78.SHAO H,FENG X L,BAO F.Text similarity computation based on deep-learning[J].Journal of Zhengzhou university(natural science edition),2020,52(1):66-71,78.
[3] 肖白,周潮,穆钢.空间电力负荷预测方法综述与展望[J].中国电机工程学报,2013,33(25):78-92,14.XIAO B,ZHOU C,MU G.Review and prospect of the spatial load forecasting methods[J].Proceedings of the CSEE,2013,33(25):78-92,14.
[4] 华蕾.基于网格化规划的上饶市经济技术开发区电力需求预测[D].北京:华北电力大学,2018.HUA L.Forecast of power demand in Shangrao economic and technological development zone based on grid planning[D].Beijing:North China Electric Power University,2018.
[5] 田怀源,张峰,王新库,等.基于灰色关联度和BP神经网络的最大负荷同时率预测方法研究[J].山东电力技术,2017,44(4):11-15,21.TIAN H Y,ZHANG F,WANG X K,et al.Prediction method research on maximum load coincidence factor based on gray relational and BP neural network[J].Shandong electric power,2017,44(4):11-15,21.
[6] 杨慢慢,王金凤,李燕青,等.改进的空间负荷预测法及其应用[J].电力科学与工程,2011,27(11):35-38.YANG M M,WANG J F,LI Y Q,et al.The improved spatial load forecasting and its application[J].Electric power science and engineering,2011,27(11):35-38.
[7] 吴怀波,程金松,陶军,等.城区配电网三级网格化规划及网格划分研究[J].国网技术学院学报,2018,21(1):1-4.WU H B,CHENG J S,TAO J,et al.Study on three-level grid planning and grid Division of urban power distribution[J].Journal of state grid technology college,2018,21(1):1-4.
[8] 刘旭,贺子尧.利用网格化规划配电网建设[J].农村电气化,2019(8):79.LIU X,HE Z Y.Planning power distribution networks construction making use of gridding[J].Rural electrification,2019(8):79.
[9] 国家电网.配电网规划设计技术导则:Q/GDW 1738-2012 [S].北京:中国电力出版社,2012:3-4.STATE GRID.The guide of planning and design of distribution network:Q/GDW 1738-2012 [S].Beijing:China Electric Power Press,2012:3-4.
[10] 黄庆键,欧周,林佳亮.关于空间电力负荷预测方法综述与展望[J].自动化应用,2017(2):79-81.HUANG Q J,OU Z,LIN J L.Review and prospect of spatial power load forecasting methods [J].Automation application,2017(2):79-81.
[11] 肖白,杨欣桐,田莉,等.计及元胞发展程度的空间负荷预测方法[J].电力系统自动化,2018,42(1):61-67.XIAO B,YANG X T,TIAN L,et al.Spatial load forecasting method based on development degree of cell[J].Automation of electric power systems,2018,42(1):61-67.
[12] 张明理,宋卓然,梁毅,等.基于饱和负荷密度的城市远景空间负荷预测[J].沈阳工业大学学报,2018,40(1):12-18.ZHANG M L,SONG Z R,LIANG Y,et al.Forecasting for urban prospective spatial load based on saturated load density[J].Journal of Shenyang university of technology,2018,40(1):12-18.
[13] 中国城市规划设计研究院.城市电力规划规范:GB/T 50293-2014 [S].北京:中国建筑工业出版社,2014:32-33.China academy of urban planning and design.Code for planning of urban electric power:GB/T 50293-2014 [S].Beijing:China Architecture and Building Press,2014:32-33.
[14] 张静,王主丁,张代红,等.配电网规划中负荷预测实际问题探讨[J].华东电力,2014,42(2):384-390.ZHANG J,WANG Z D,ZHANG D H,et al.Actual load forecasting problems in distribution network planning[J].East China electric power,2014,42(2):384-390.
基本信息:
DOI：10.13705/j.issn.1671-6841.2020023
中图分类号:TM715
引用信息:
[1]蒋建东,李瑞杰.配电网网格化规划中空间负荷预测方法研究[J],2021,53(01):120-126.DOI:10.13705/j.issn.1671-6841.2020023.
基金信息:
国家自然科学基金项目(51507155)