Optimization of short-term wind power prediction of Multi-kernel Extreme Learning Machine based on Sparrow Search Algorithm

Abstract

Aiming at the problem that the single kernel function of kernel extreme learning machine (KELM) cannot adapt to the variable actual wind power. This paper proposes a modified prediction model which can increase the accuracy of prediction. The prediction model uses multiple kernel functions instead of a single kernel function and optimizes the kernel parameters by using a sparrow search algorithm (SSA). Finally, through the simulation and comparison experiments, the proposed prediction model has better prediction accuracy than the conventional prediction model.