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基于历史天气的区域电网负荷预测

Research on regional power grid load forecasting based on historical weather
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摘要 随着社会经济的迅速发展,人们对电能的需要日益增加,但是在电网运行中,常常会出现电力产能过剩或者不足的情况,为保证电力系统安全稳定、经济运行,就必须掌握各种区域电网负荷的变化规律和发展趋势。论文对重庆市区供电分公司供电区域电网中长期负荷进行预测,提出一种预测区域电网中长期负荷的方法,即一种基于前12个月历史天气条件和区域电网负荷关联关系的多元非线性拟合的特征参数因子曲线的中长期负荷预测方法,建立基于不同算法的多种预测模型,通过归一化处理,得到的区域电网中长期负荷预测的精度高,与实际区域电网负荷之间的误差小,对于区域电网中长期负荷预测分析具有重要参考利用价值。 With the rapid development of social economy,people's need for electric energy is increasing day by day.However,in the operation of power grid,there is often excess or insufficient power capacity.Therefore,in order to ensure the safety,stability and economic operation of power system,it is necessary to master the change law and development trend of various regional power grid loads.This paper has forecast the medium and long term load of the regional power grid of the Chongqing Power Supply Branch,and puts forward a method to predict the medium and long term load of the regional power grid,namely a kind of history based on the previous 12 months the weather conditions and the regional power grid load correlation multivariate nonlinear fitting the characteristic parameters of factor curves of medium and long term load forecasting method,and establishes a variety of forecasting models based on different algorithms and through the normalization processing,the regional power network medium and long term load forecasting accuracy is high and the error between the actual regional power network load is small,and has important reference and application value for the regional power network medium and long term load forecasting analysis.
作者 董莉娜 张志劲 王茂政 DONG Lina;ZHANG Zhijin;WANG Maozheng(State Key Laboratory of Power Transmission Equipment&System Security and New Technology(Chongqing University),Chongqing 400044,China;State Grid Chongqing Electric Power Company,Chongqing 400015,China)
出处 《中国测试》 CAS 北大核心 2024年第6期183-190,共8页 China Measurement & Test
基金 国网重庆市电力公司科技项目(2019渝电科技14#)。
关键词 中长期负荷预测 归一化 多元非线性拟合 历史天气条件 区域电网 medium and long term load forecasting the normalized multivariate nonlinear fitting historical weather conditions regional power grid
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