Photovoltaic Power Combination Prediction Model Based on GA-VMD-ESN
In order to reduce the impact of the randomness,volatility,and intermittency of photovoltaic power generation on grid scheduling and economic benefits,a combined model for photovoltaic power prediction is proposed.Based on genetic algorithm(GA)to optimize the key parameters of variable mode decomposition(VMD),this model first decomposes the non-stationary time series of photovoltaic power into VMD,and optimizes the number of modes and penalty coefficients through GA to ensure the best decomposition effect.Apply Echo State Network(ESN)for modeling the fluctuation characteristics of each modality.Finally,the predicted results of each mode are superimposed and reconstructed to obtain the final predicted value of photovoltaic power.Through experimental verification,it has been proven that the combined prediction model has superior accuracy and performance.
万方数据
维普
