汪付华,周后福,戴金源,张屏,董平安,张怀念,刘璐.基于经济气象因素的月用电负荷预测模型研究[J].电力需求侧管理,2020,22(5):78-82 |
基于经济气象因素的月用电负荷预测模型研究 |
Study on the forecasting model of monthly power load based on economic and meteorological factors |
投稿时间:2020-05-08 修订日期:2020-07-16 |
DOI:10. 3969 / j. issn. 1009-1831. 2020. 05. 015 |
中文关键词: 用电负荷 趋势负荷 气象负荷 预测模型 |
英文关键词: electric load trend load meteorological load mid⁃term prediction model |
基金项目:安徽省公益性科研项目(1604f0804002);安徽省气象局科技基金(KM201709) |
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中文摘要: |
基于 2012—2018 年安徽省淮北地区月用电负荷、宏观经济数据和气象观测资料,运用相关分析、多元回归分析和曲线拟合等方法,将实际用电负荷分解为趋势负荷和波动负荷,分析趋势负荷与经济数据的关系建立基于经济指标的趋势负荷预测模型,拟合率达到 99.3%;研究波动负荷与气象因子的关系建立基于气象因子的波动负荷预测模型,拟合率达到 97.8%;经测试模型的泛化能力较高,符合设计要求。将研究成果作为新的服务手段为电力部门提供更加专业、定量的服务产品,为淮北电网运营调度提供科学依据,取得了明显的社会经济效益。 |
英文摘要: |
Based on the electric load, macroeconomic data and meteorological observation data in Huaibei of Anhui from 2012 to 2018, some equations are built by using correlation analysis, multiple regression analysis and curve fitting method. The actual power load is divided into trend load and fluctuating load. The trend load forecast model is established based on economic index after the relationship between trend load and economic data is analyzed. The fitting rate of the model reaches 99.3% . The forecast model of fluctuating load is built based on meteorological factors after the relationship between fluctuating load and meteorological factors are analyzed. The fitting rate of the model reaches 97.8%.The application of these results provides scientific basis for operation and dispatch of Huaibei Power Grid, and it has achieved obvious social and economic benefits. |
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