Title: Real time prediction of solar radiation of Indore region using machine learning algorithms

Authors: Sanjiv Kumar Jain; Kaustubh Yawalkar; Prakhar Singh; Advait Apte

Addresses: Electrical Engineering Department, Medi-Caps University, Indore, India ' Electrical Engineering Department, Medi-Caps University, Indore, India ' Electrical Engineering Department, Medi-Caps University, Indore, India ' Electrical Engineering Department, Medi-Caps University, Indore, India

Abstract: The most crucial data requirement for all solar energy researches is solar radiation. As solar radiation is the quantity which is dependent on time, the desired power output of any solar power plant is also dependent on time. The objective of this paper is to utilise machine learning models to estimate the solar radiations on daily data of Indore region (22.7196°N, 75.8577°E). The speed of wind, temperature, pressure, humidity along with solar radiation are used and applied in the process of prediction. The evaluation of the model is done in terms of prediction efficiency. In the work, boosted decision tree algorithm is used for the solar radiation prediction, which gives an accuracy of 96.9%. Also, the multiple linear regression algorithm is utilised in the work for the real time estimation of hourly solar radiations. The method gives an accuracy of 91.8%.

Keywords: solar radiation; linear regression; boosted decision tree; machine learning.

DOI: 10.1504/IJESMS.2021.10039532

International Journal of Engineering Systems Modelling and Simulation, 2021 Vol.12 No.4, pp.264 - 270

Received: 11 Feb 2021
Accepted: 26 Feb 2021

Published online: 22 Dec 2021 *

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