基于气象因素的长江经济带湖北段夏季日最大电力负荷预测  

Prediction of Summer Daily Maximum Power Load in the Hubei Section of the Yangtze River Economic Belt Based on Meteorological Factors

作　　者：王丽娟 任永建 王俊超[2] 欧阳威 WANG Lijuan;REN Yongjian;WANG Junchao;OUYANG Wei(Hubei Meteorological Service Center,Wuhan 430205,Hubei,China;Hubei Key Laboratory for Heavy Rain Monitoring and Warning Research,Institute of Heavy Rain,China Meteorological Administration,Wuhan 430205,Hubei,China)

机构地区：[1]湖北省气象服务中心,湖北武汉430205 [2]中国气象局武汉暴雨研究所暴雨监测预警湖北省重点实验室,湖北武汉430205

出　　处：《南方能源建设》2024年第1期133-142,共10页Southern Energy Construction

基　　金：中国气象局气候变化专项“极端事件对长江经济带湖北段电网负荷的影响”(CCSF202033)。

摘　　要：[目的]利用气候预测模式的气温数据对未来长江经济带湖北段武汉、黄石、宜昌夏季日最大电力负荷进行预测。[方法]基于武汉、黄石、宜昌2008~2019年逐日最大电力负荷数据、同期平均气温、最高气温、最低气温等气象要素资料以及RegCM4区域气候模式预测数据,对3个地区的气象敏感电力负荷特性进行分析。在此基础上,通过回归法和群粒子优化BP神经网络算法,对未来(2020~2096年)日最大电力负荷进行定量滚动预测。[结果]结果表明,夏季平均气温与气象敏感负荷关联度最大。预测武汉和宜昌两地的夏季日最大电力负荷相似,两种预测值较近10 a日最大电力负荷稳步增长,回归预测的增长率要略高于神经网络预测;宜昌增长率比武汉高,最高超过40%。黄石日最大电力负荷的预期值较其他两地呈现出明显不同预测结果。[结论]预测长江经济带的中大型城市夏季日最大电力负荷的变化规律,有助于规划未来所需额外的电网容量。[Introduction]This study focuses on the prediction of summer daily maximum power load in Wuhan,Huangshi,and Yichang of the Hubei section in the Yangtze River Economic Belt based on climatic forecast model temperature data.[Method]By analyzing the daily maximum power load data from 2008 to 2019,along with meteorological elements such as average temperature,maximum temperature,minimum temperature,and regional climate model(RegCM4)forecast data,the characteristics of meteorologically sensitive power load in the three regions were analyzed.Regression analysis and a group-particle optimized back-propagation(BP)neural network algorithm were used to quantitatively predict the future(from 2020 to 2096)daily maximum power load.[Result]The results indicate that there is a significant correlation between summer average temperature and meteorologically sensitive load.The predicted values of regression prediction slightly higher than that of neural network prediction.The growth rate in Yichang is higher than that in Wuhan,exceeding 40%at its peak.The expected values of the daily maximum power load in Huangshi show distinctly different prediction results compared to the other two locations.[Conclusion]Predicting the variation patterns of summer daily maximum power load in medium-to-large cities along the Yangtze River Economic Belt is beneficial for planning the required additional grid capacity in the future.

关 键 词：长江经济带湖北段 气象因素 模式预测 最大电力负荷 神经网络 

分 类 号：TM7[电气工程—电力系统及自动化] S42[农业科学—植物保护]