Prediction of the Speed and Wind Direction Using Machine Learning

Author:

Pattanaik Balachandra,Manikandan S.,Peniel Pauldoss S.,Gobinath S.

Abstract

Abstract The wind is a free energy source; however, its high unpredictability is a significant integration problem of large wind power plant into an energy system. In a wind conversion system, the wind speeds are a vital power-generated tracking, regulation, schedules and dispatch and satisfy consumer requirements. This paper proposes using the machine learning (ML) based ant colony optimization (ACO) method for the wind speed prediction. A correlation among predicted and real data from climate models showed strong consensus. The significance of the current research depends on its ability to forecast wind speeds, a crucial precursor to performing successful incorporation of wind power.

Publisher

IOP Publishing

Subject

General Physics and Astronomy

Reference21 articles.

1. Wind power forecasting based on daily wind speed data using machine learning algorithms.;Demolli;Energy Conversion and Ma nagem en t,2019

2. Current methods and advances in the forecasting of wind power generation.;Foley;Renewable Energy,2012

3. Probabilistic forecasting of wind power generation using extreme learning machine.;Wan;IEEE Transactions on Power Systems,2013

4. A review on the forecasting of wind speed and generated power.;Lei;Renewable and Sustainable Energy Reviews,2009

5. Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm.;Li;Journal of Cleaner Produ ct ion,2020

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