| 引用本文: | 李元诚,王 蓓,王旭峰.基于和声搜索-高斯过程混合算法的光伏功率预测[J].电力自动化设备,2014,34(8): |
| LI Yuancheng,WANG Bei,WANG Xufeng.Photovoltaic power forecasting based on harmony search and Gaussian process algorithms[J].Electric Power Automation Equipment,2014,34(8): |
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| 摘要: |
| 光伏发电并网后会对电网产生冲击，影响电网稳定。通过对光伏发电功率的特性分析，在研究高斯过程算法原理的基础上，建立了基于高斯过程的光伏发电功率预测模型。针对传统高斯过程中优化超参数采用共轭梯度法存在的缺陷，提出采用和声搜索算法代替共轭梯度法，得到一种基于和声搜索优化的混合高斯过程模型。仿真结果表明，采用和声搜索优化后的高斯过程混合算法比传统高斯过程方法的预测精度更高。 |
| 关键词: 并网 光伏 发电 输出功率 预测 高斯过程 和声搜索 优化 模型 |
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| Photovoltaic power forecasting based on harmony search and Gaussian process algorithms |
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LI Yuancheng, WANG Bei, WANG Xufeng
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State Key Laboratory for Alternate Electrical Power System with Renewable Energy Sources， North China Electric Power University，Beijing 102206，China
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| Abstract: |
| The integration of photovoltaic power generation into power grid has impact on its stability. The power characteristics of photovoltaic power generation are analyzed and the principle of Gaussian process algorithm is researched，based on which，a photovoltaic power forecasting model is built. Instead of the conjugate gradient method，the harmony search algorithm is applied in the built model to optimize the hyper-parameter. Simulative results show that，the Gaussian process algorithm optimized by the harmony search has higher accuracy than the traditional one. |
| Key words: grid-connection photovoltaic cells electric power generation output power forecasting Gaussian process harmony search optimization models |
