Prediction of the Speed and Wind Direction Using Machine Learning. Issue 4 (July 2021)

• Record Type: Journal Article
• Authors: Pattanaik, Balachandra; Manikandan, S.; Peniel Pauldoss, S.; Gobinath, S.
• Is Part Of: Journal of physics. Volume 1964:Issue 4(2021)
• Publication Date: 2021-07
• Subjects: ML system -- wind direction -- wind speed and ACO; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1964/4/042064
• Languages: English
• ISSNs: 1742-6588

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.