基于优化相空间重构技术的风电场发电功率预测研究

Wind Power Prediction Based on Technology of Advanced Phase Space Reconstruction

大规模风电的接入将对电网的规划建设、分析控制、经济运行以及电能质量等方面产生一定的影响,较为准确的风电功率预测可减少电网旋转备用,为电网运行调度提供可靠的依据。以中国某风电场为例,对风力发电功率的超短期预测方法进行了研究,提出了以混沌理论为基础、基于相空间重构的风电出力混沌时间序列预测的方法,对相空间重构参数的优化进行了综合计算,定性分析了风电出力时间序列的混沌特征,同时对应用嵌入维空间的具体预测方法进行了研究。实际算例表明该综合方法具有较高的预测精度。

Integration of large-scale wind-farm in power grid will impact grid planning, construction, operation and energy quality. Wind power prediction can help reduce the quantity of spinning reserve and improve the reliability of grid operation. This paper proposed a method of wind power prediction based on chaotic theory and the technology of phase space reconstruction. Optimal parameters for phase space reconstruction and prediction method were studied. The simulation result verified that these methods effectively improved the wind power prediction accuracy.