An improved whale algorithm for power load forecasting based on adaptive weight adjustment

Abstract

With the progress of the times, people have higher and higher expectations for the electric power system in the new era. To meet the new requirements, improving load forecasting capabilities has become an important part of the process. In this article, an improved whale algorithm based on adaptive weight adjustment is presented to predict user load, using a Cubic-map strategy to achieve better population effect, combining the whale algorithm and the BP algorithm so as to improve the rate of convergence and prediction accuracy of the algorithm. Simulation software is used to conduct simulation experiments on multiple algorithms. From the experimental data, it can be concluded that compared with a single algorithm, the algorithm proposed in this paper has a stronger ability to find the optimal value within the effective boundary. Both the rate of convergence is faster, and it has higher accuracy.