| 基于蚁群优化的最小二乘支持向量机风速预测模型研究 |
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| 引用本文： | 曾杰,张华. 基于蚁群优化的最小二乘支持向量机风速预测模型研究[J]. 太阳能学报, 2011, 32(3): 296-300 |
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| 作者姓名： | 曾杰 张华 |
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| 作者单位： | 华北电力大学可再生能源学院,北京,102206 |
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| 摘 要： | 基于最小二乘支持向量机理论,建立风速预测模型。同时,由于最小二乘支持向量机参数选取尚无有效方法,该文尝试采用蚁群算法理论来进行参数优化选择。选取某风场前四天的实测风速(采样间隔30min),应用所建立的风速预测模型,来预测第五天的48个风速值,其预测的平均绝对百分比误差仅为9.53%,预测效果较理想,验证了应用蚁群优化算法理论与最小二乘支持向量机理论进行风速预测的可行性,可为风电场规划选址和风力发电功率预测等提供理论支持。
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| 关 键 词： | 风速预测 最小二乘支持向量机 蚁群优化算法 风电场 风力发电 |
WIND SPEED FORECASTING MODEL STUDY BASED ON LEAST SQUARES SUPPORT VECTOR MACHINE AND ANT COLONY OPTIMIZATION |
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| Zeng Jie,Zhang Hua. WIND SPEED FORECASTING MODEL STUDY BASED ON LEAST SQUARES SUPPORT VECTOR MACHINE AND ANT COLONY OPTIMIZATION[J]. Acta Energiae Solaris Sinica, 2011, 32(3): 296-300 |
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| Authors: | Zeng Jie Zhang Hua |
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| Affiliation: | Zeng Jie,Zhang Hua(School of Renewable Energy,North China Electric Power University,Beijing 102206,China) |
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| Abstract: | This paper based on Least Squares Support Vector Machine theory to build the wind speed forecasting model.Meanwhile,as there is still no effective choice method of Least Squares Support Vector Machine parameter,this paper tried to use Ant Colony Algorithm theory to optimization choice for parameter.And last,use wind farm observed wind speed(sampling interval is 30 minutes) of the day before four days to forecast the 48ind wind speed of the fifth day through this paper's wind forecasting model,and prediction... |
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| Keywords: | wind speed forecasting Least Squares Support Vector Machine Ant Colony Optimization Algorithm wind farm wind power |
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