Analysis of power load combination forecasting model based on improved particle swarm optimization

As for the particularity of the power load forecasting, this paper presents a new power load combination forecasting model, that is, first select several basic load forecasting methods to forecast the results, and then select an improved particle swarm optimization (PSO) algorithm to optimize the weights of single-forecast results. According to the weights, calculate the weighted average of the single-forecast results, and the obtained value is the load forecast value. The empirical results show that the combination forecasting model combines the advantages of various methods, and greatly improves the accuracy of power load forecasting.