| 改进粒子群算法在中长期电力负荷组合预测模型中的应用 |
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| 引用本文： | 李小龙,李郁侠,师彪,牛艳利,王煜.改进粒子群算法在中长期电力负荷组合预测模型中的应用[J].武汉大学学报(工学版),2011,44(3):380-382,387. |
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| 作者姓名： | 李小龙 李郁侠 师彪 牛艳利 王煜 |
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| 作者单位： | 西安理工大学水利水电学院,陕西西安,710048 |
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| 摘 要： | 为提高电力负荷预测的精度,提出了基于改进粒子群算法的电力负荷组合预测模型求解方法.该方法以回归分析、比例系数、灰色模型为基础建立负荷组合预测模型,利用改进粒子群算法优化组合预测模型的权值,并与单个预测模型进行比较.预测结果表明,基于改进粒子群算法的电力负荷组合预测模型运算速度快,预测精度高,相对误差小.
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| 关 键 词： | 改进粒子群算法 电力负荷预测 组合预测 相对误差 |
Application of improved particle swarm optimization to mid-long-term power load combination forecasting model |
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| LI Xiaolong,LI Yuxia,SHI Biao,NIU Yanli,WANG Yu.Application of improved particle swarm optimization to mid-long-term power load combination forecasting model[J].Engineering Journal of Wuhan University,2011,44(3):380-382,387. |
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| Authors: | LI Xiaolong LI Yuxia SHI Biao NIU Yanli WANG Yu |
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| Affiliation: | LI Xiaolong,LI Yuxia,SHI Biao,NIU Yanli,WANG Yu(College of Water Resources and Hydropower Engineering,Xi'an University of Technology,Xi'an 710048,China) |
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| Abstract: | To forecast power load accurately,the power load combination forecasting model method based on improved particle swarm optimization algorithm is proposed.This method takes regression analysis,proportionality coefficient and grey model forecasting as the basic forecasting model.It optimizes the weight of combination forecasting through the improved particle swarm optimization algorithm.Comparing the forecasting data with the single model's data,the results show that the operation speed of combination forecas... |
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| Keywords: | improved particle swarm optimization power load forecasting combination forecasting relative error |
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