Machine Learning-Based Predictive the Forecasting of Short Term Wind Speed

Abstract

Abstract As a possible emerging technology for electricity generation, wind power is rapidly evolving world’s mainstream influence. However, the inherent spontaneous wind instability poses great obstacles to stable grid usage and power supply stability. One way of efficiently addressing the wind instability problem is to enhance accurate wind velocity forecasts. However, the intrinsic regularity of wind speed data cannot be for the bulk of the wind speed estimation method. Therefore, this paper introduces machine learning (ML) based genetic algorithm (GA) and the Short-term Wind Speed Prediction Model, which can effectively improve wind speed prediction accuracy. The work of study will help evaluate the power grid risks adequately. The appropriate electricity system divisions are expected to create a realistic generation schedule, minimize cost effectively, and significantly encourage green-energy growth.