
三峡大学电气与新能源学院
Published:2025
移动端阅览
[J]. 2025, (4): 88-95.
行政区划变更等原因将限制历史季度用电量数量,对其准确预测提出了挑战.为此,本文提出贫样本约束下的季度用电量最优组合预测模型.首先,将季度用电量数据分解为长期、周期、随机3类分量,应用最小二乘法和综合精度分为各类分量选取最佳拟合函数.其次,对各拟合函数加权组合,并应用果蝇优化算法求取最优组合系数,优化综合精度分,得出该模型参数.然后,收集重庆市直辖初期4年共16组季度用电数据验证本文模型,结果表明该模型对第4年季度用电量预测值的平均绝对百分比误差可达8.962%
低于现有4类预测模型.最后,将本文模型应用至吉林和福建,结果表明本文模型的平均绝对百分比误差最小值可至2.472%.
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