基于和声搜索-高斯过程混合算法的光伏功率预测
发布时间:2018-11-21 10:53
【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。
[Abstract]:Photovoltaic generation will have an impact on the grid after the grid, affecting the stability of the grid. Based on the analysis of the characteristics of photovoltaic power generation, and on the basis of studying the principle of Gao Si process algorithm, a photovoltaic power prediction model based on Gao Si process is established. In order to overcome the shortcomings of conjugate gradient method in the traditional Gao Si process, the harmonic search algorithm is proposed to replace the conjugate gradient method, and a hybrid Gao Si process model based on harmonic search optimization is proposed. The simulation results show that the hybrid algorithm of Gao Si process optimized by harmonic search is more accurate than that of the traditional Gao Si process method.
【作者单位】: 华北电力大学新能源电力系统国家重点实验室;
【分类号】:TM615
本文编号:2346761
[Abstract]:Photovoltaic generation will have an impact on the grid after the grid, affecting the stability of the grid. Based on the analysis of the characteristics of photovoltaic power generation, and on the basis of studying the principle of Gao Si process algorithm, a photovoltaic power prediction model based on Gao Si process is established. In order to overcome the shortcomings of conjugate gradient method in the traditional Gao Si process, the harmonic search algorithm is proposed to replace the conjugate gradient method, and a hybrid Gao Si process model based on harmonic search optimization is proposed. The simulation results show that the hybrid algorithm of Gao Si process optimized by harmonic search is more accurate than that of the traditional Gao Si process method.
【作者单位】: 华北电力大学新能源电力系统国家重点实验室;
【分类号】:TM615
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