Real time prediction of solar radiation of Indore region using machine learning algorithms. (17th December 2021)

• Record Type: Journal Article
• Authors: Jain, Sanjiv Kumar; Yawalkar, Kaustubh; Singh, Prakhar; Apte, Advait
• Is Part Of: International journal of engineering systems modelling and simulation. Volume 12:Number 4(2021)
• Page Start: 264
• Page End: 270
• Publication Date: 2021-12-17
• Subjects: solar radiation -- linear regression -- boosted decision tree -- machine learning; Engineering systems -- Computer simulation -- Periodicals; Engineering systems -- Mathematical models -- Periodicals; 620.0042
• Languages: English
• ISSNs: 1755-9758

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%.