气象因子相对危险度在电网用电负荷预测中的应用  

Application of Relative Risk of Meteorological Factors in Power Grid Electricity Load Forecasting

作　　者：曲晓黎[1,2,3] 尤琦 李文晴 杨琳晗 王洁 张金满 高泽田 周朔 QU Xiaoli;YOU Qi;LI Wenqing;YANG Linhan;WANG Jie;ZHANG Jinman;GAO Zetian;ZHOU Shuo(Key Laboratory of Weather and Ecological Environment of Hebei Province,Shijiazhuang 050021,Hebei,China;China Meteorological Administration Xiong'an Atmospheric Boundary Layer Key Laboratory,Baoding 071800,Hebei,China;Hebei Provincial Meteorological Service Center,Shijiazhuang 050021,Hebei,China)

机构地区：[1]河北省气象与生态环境重点实验室,河北石家庄050021 [2]中国气象局雄安大气边界层重点开放实验室,河北保定071800 [3]河北省气象服务中心,河北石家庄050021

出　　处：《南方能源建设》2024年第1期166-175,共10页Southern Energy Construction

基　　金：河北省省级科技计划项目“导线覆冰和风偏气象灾害精准预警技术研究”(22375405D)。

摘　　要：[目的]准确高效的短期用电负荷预测是保证电力系统安全可靠运行的前提,也是电网合理安排发电计划的依据,因此研究气象与用电负荷的关系对负荷预测的工作具有重要意义。[方法]以石家庄为例,利用国网河北省某电力公司提供的2013年1月1日至2021年12月31日逐15 min用电负荷资料,以及对应的石家庄站气象观测资料,分析日用电负荷峰值的时间变化特征,重点分析了当日用电负荷峰值较前1日用电负荷峰值变幅超过10%的样本对应的气象条件。采用Spearman秩相关方法分析石家庄日用电负荷峰值与前1日气象要素的相关关系,得到相关性显著的气象要素。利用平滑曲线拟合法绘制各相关性显著的气象要素对次日用电负荷峰值的响应曲线,分析得出随着各气象要素的变化日用电负荷峰值变化趋势以及响应阈值。按不同阈值区间,基于泊松分布计算得出石家庄地区各气象要素对日用电负荷峰值变化的相对危险度,进而揭示石家庄地区各气象要素在不同阈值区间发生单位变化造成的日用电负荷峰值的变化幅度,即不同气象要素的变化对日用电负荷峰值变化的定量影响。[结果]以气温为例,当日平均气温、日最高气温、日最低气温高于阈值时,每上升1℃,次日用电负荷峰值的相对危险度分别增加2.25%、1.92%、2.07%;低于阈值时,每上升1℃,次日用电负荷峰值的相对危险度分别减少0.62%、0.57%、0.60%。[结论]基于不同气象要素对石家庄地区日用电负荷峰值的相对危险度提出1种次日用电负荷峰值的预测方法,利用2022年逐日用电负荷和气象资料进行检验,发现预测效果可以满足日常电力气象服务需求。[Introduction]Accurate and efficient short-term electricity load forecasting is a prerequisite for ensuring the safe and reliable operation of power system,and it is also the basis for the rational arrangement of power generation plans in the power grid.Therefore,studying the relationship between meteorology and electricity load is of great significance for load forecasting.[Method]Based on the electricity load data at 15 min intervals during the period between January 1 of 2013 and December 31 of 2021 provided by the State Grid Hebei Electric Power Co.,Ltd.as well as the corresponding meteorological observation data of Shijiazhuang station,this paper analyzed the temporal variation characteristics of daily peak electricity load in Shijiazhuang,and in particular,the meteorological conditions corresponding to the samples with a daily peak electricity load that was 10%higher than that of the previous day were analyzed.The Spearman's rank correlation method was used to analyze the correlation between daily peak electricity load in Shijiazhuang and the meteorological factors of the previous day,and significantly correlated meteorological factors were identified.The response curves of the significantly correlated meteorological factors to the next day's peak electricity load were drawn using the smooth curve fitting method,and the analysis revealed the changing trend of daily peak electricity load with the variations of meteorological factors,as well as the response thresholds.For different threshold ranges,the relative risk of meteorological factors to the changes of the daily peak electricity load was calculated based on the Poisson distribution.On this basis,the variation magnitudes of daily peak electricity load caused by per unit change in each meteorological factor within different threshold ranges in Shijiazhuang were calculated,that is,the quantitative impacts of the changes in different meteorological factors on the variation of daily peak electricity load were revealed.[Result]Taking temperature as an exampl

关 键 词：负荷预测 Spearman秩相关 相对危险度 定量分析 预测检验 

分 类 号：TM7[电气工程—电力系统及自动化] P49[天文地球—大气科学及气象学]