文章摘要
向德军,张维静,冯歆尧,杨秋勇,蔡元纪.考虑特征值细分的广义加性短期负荷预测模型[J].电力需求侧管理,2023,25(1):46-51
考虑特征值细分的广义加性短期负荷预测模型
Generalized additive short-term load forecasting model considering eigenvalue subdivision
投稿时间:2022-09-30  修订日期:2022-11-10
DOI:10.3969/j.issn.1009-1831.2023.01.008
中文关键词: 短期负荷预测  时间序列  特征值细分  广义加性模型
英文关键词: short-term load forecasting  time series  eigenvalue subdivision  generalized additive model
基金项目:广东电网有限责任公司科技项目(GDKJXM20182328)
作者单位
向德军 广东电网有限责任公司广州 510000 
张维静 清华大学 电机系北京 100084 
冯歆尧 广东电网有限责任公司广州 510000 
杨秋勇 广东电网有限责任公司广州 510000 
蔡元纪 清华大学 电机系北京 100084 
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中文摘要:
      准确的负荷预测是保障电力市场有序运行的关键,针对单一因素预测环境受限、综合模型对变量的拆分及交互作用考虑欠周的问题,提出建立考虑温度、节假日、负荷等细分特征变量的广义加性短期负荷预测模型。首先,细分并测算了不同因素与负荷的相关系数,依据相关度筛选特征变量;其次,确定负荷波动基函数,针对细分特征变量分别建模,形成整体预测模型;最后,利用广州实际运行数据测算分析。实例表明,基于特征值细分的广义加性模型预测效果更佳,是短期负荷预测的一种有效方法。
英文摘要:
      Accurate load forecasting is the key to ensure the orderly operation of the power market. In view of the limited environment of single factor forecasting and the ill- considered problems of the split and interaction of variables in the comprehensive model, a generalized additive short- term load forecasting model considering subdivided characteristic variables such as temperature, holidays and load is proposed. Firstly, the correlation coefficients of different factors and loads are subdivided and calculated,and the eigenvalues are selected according to the correlation degree. Secondly, the load fluctuation basis function is determined,and the whole forecasting model is formed according to the subdivided characteristic variables. Finally, the actual operation data of Guangzhou is used to calculate and analyze. The example shows that the generalized additive model based on eigenvalue subdivision is an effective method for short-term load forecasting.
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