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光伏发电功率预测对光能充分利用具有重要的意义,因此本文提出一种采用基于改进粒子群优化最小二乘支持向量机(LSSVM)的预测模型,对数据进行筛选并归一化处理后,采用改进粒子群算法优化最小二乘支持向量机两个影响回归性能的参数,对光伏发电功率进行预测。通过仿真和实际数据验证,该模型有良好的预测能力,对实际光伏发电系统具有指导意义。
Therefore, this paper presents a prediction model based on improved particle swarm optimization least squares support vector machine (LSSVM), after screening and normalizing the data, we use the Two improved particle swarm optimization algorithms, least squares support vector machine, are used to predict the performance of photovoltaic power generation. Through simulation and actual data verification, the model has good predictive ability and is of guiding significance for the actual photovoltaic power generation system.