基于布谷鸟搜索优化的光伏电站辐照强度预测

针对光伏电站日前小时短期辐照强度的预测准确性问题,且考虑到支持向量机的学习参数对预测模型的性能有较大影响,为进一步提高数据的预测精度,利用布谷鸟搜索算法对支持向量机的惩罚因子c和核参数g进行优化,提出了一种基于布谷鸟搜索算法和支持向量回归的组合预测方法。仿真结果表明:该方法大大提高了光伏辐照强度预测的准确性和精度,可行且高效,适用于光伏在线预测。

Prediction of radiation intensity for photovoltaic power plant based on cuckoo searchoptimization

Aiming at the problem of the prediction accuracy for day ahead short- term radiationintensity of photovoltaic power plants, and considering the learning parameters of support vectormachine(SVM) have great influence on the performance of predicting model, in order to improvefurther the accuracy of prediction data, introduces the cuckoo search algorithm to optimize the penaltyfactor c and the kernel parameter g of SVM, puts forward a combined forecasting method based oncuckoo search and support vector regression. The simulation result shows that this method canimprove greatly the prediction accuracy and precision of photovoltaic radiation intensity, it '' s feasibleand efficient, can apply to photovoltaic online prediction.