| 基于PCA-LMD-WOA-ELM的短期光伏功率预测 |
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| 引用本文： | 王鹏翔,沈娟,王菁旸,林重驰.基于PCA-LMD-WOA-ELM的短期光伏功率预测[J].陕西电力,2022,0(6):72-78. |
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| 作者姓名： | 王鹏翔 沈娟 王菁旸 林重驰 |
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| 作者单位： | （1.三峡大学电气与新能源学院，湖北宜昌 443002；2.三峡大学土木与建筑学院，湖北宜昌 443002） |
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| 摘 要： | 对光伏发电功率进行准确预测，可减弱其并入电网的波动性，有利于电网对新能源发电的调度。基于主成分分析法和局部均值分解相结合的鲸鱼优化算法，构造优化后的极限学习机模型，并使用该模型对光伏发电短期功率进行预测。先用主成分分析法对影响光伏发电功率的因素进行筛选，并使用局部均值分解对选取的主要影响因素及发电功率序列数据进行分解；然后基于子序列使用鲸鱼优化建立极限学习机模型；最后将各序列短期预测结果叠加获得光伏发电短期功率预测结果。通过仿真验证及对比分析，说明该预测方法具有较高的预测精准度。
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| 关 键 词： | 光伏发电 主成分分析 局部均值分解 鲸鱼优化算法 极限学习机 短期功率预测 |
Short Term Photovoltaic Power Prediction Based on PCA-LMD-WOA-ELM |
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| WANG Pengxiang,SHEN Juan,WANG Jingyang,LIN Zhongchi.Short Term Photovoltaic Power Prediction Based on PCA-LMD-WOA-ELM[J].Shanxi Electric Power,2022,0(6):72-78. |
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| Authors: | WANG Pengxiang SHEN Juan WANG Jingyang LIN Zhongchi |
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| Affiliation: | （1. College of Electrical and New Energy，China Three Gorges University，Yichang 443002， China；2. College of Civil Engineering and Architecture，Three Gorges University，Yichang 443002， China） |
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| Abstract: | Accurate power prediction of photovoltaic power generation can reduce the volatility of its integration into power grid， which is conducive to the dispatching of new energy power generation. Based on whale optimization algorithm combining principal component analysis and improved local mean decomposition，the optimized extreme learning machine model is constructed，and the model is used to predict short-term power of photovoltaic power generation. Firstly， the factors affecting photovoltaic power generation are screened by principal component analysis， and the selected main influencing factors and power generation sequence data are decomposed by local mean decomposition. Then，the extreme learning machine model is established by whale optimization algorithm based on subsequences. Finally，the short-term power prediction results of photovoltaic power generation are obtained by superimposing the short-term prediction results of each sequence. Simulation and analysis verify the high prediction accuracy of proposed prediction method. |
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| Keywords: | photovoltaic power generation principal component analysis local mean decomposition whale optimization algorithm extreme learning machine short term power prediction |
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