灰色-马尔可夫链统计组合模型在光伏发电功率短期预测中的应用

Photovoltaic power short-term forecasting based on Gray-Markov chain statistical combination model

光伏系统输出功率具有随机性和波动性的特点,光伏系统并网以后可能引起运行和可靠性问题。提前对光伏发电功率进行准确预测有利于电力部门及时调度和保证电能质量,从而保证电网的安全运行。在分析灰色预测模型局限性的基础上,将灰色-马尔可夫链组合预测模型应用到光伏功率短期预测中,并阐述了其建模原理。通过对灰色模型拟合值的相对残差序列进行分析及建立马尔可夫链状态转移概率矩阵,得出灰色-马尔可夫链预测模型。通实际算例分析,证验了所提组合模型的准确性和简便性。

The operation and reliability problems may arise after grid integration of photovoltaic system, due to the characteristics of PV power, such as volatility and randomness. Predicting the photovohaic power accurately in ad- vance will benefit the power sector to adjust the scheduling plan timely to ensure power quality, and then ensure the grid to operate safely. Based on the analysis of the limitations of the gray forecasting model, the Gray-Markov chain combination forecasting model was applied to predict the short-term photovoltaic p3wer, and described its modeling principles. Gray-Markov chain model can be drawn through analyzing the relative residuals of the fitted values of the gray model and establishing the state transition probability matrix. The accuracy and simplicity of the proposed combi- nation model are verified through analyzing the practical examples.