Solar Mapping of India using Support Vector Machine

R. Meenal, A. Immanuel Selvakumar, S. Berclin Jeyaprabha, E. Rajasekaran

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Accurate knowledge of global solar radiation (GSR) data is necessary for various solar energy based applications. However, in spite of its importance, the number of solar radiation measuring stations is comparatively rare throughout the world due to financial cost and difficulties in measurement techniques. The objective of this current study is to assess the solar energy potential and to develop solar resource mapping of India without utilizing the direct measurement techniques. GSR is predicted with commonly available meteorological parameters like minimum and maximum temperature as its inputs by using Support Vector Machine (SVM) based solar radiation model. The SVM model is validated with measured data from India Meteorological Department (IMD). This study simplifies the major challenge of preparing GSR data for various solar energy applications in a big country like India. Also the life cycle cost of Solar PV is analyzed in India. The payback period will be around 3 years for an annually solar radiation of range from 3.5 to 6 kWh/m2/day. This work eliminates the requirement of costly pyranometer to get GSR data. Solar resource mapping of India is developed without direct measurement technique thus avoids GSR data recording, daily maintenance and subsequently the increasing cost of GSR data collection.
Original languageEnglish
Title of host publicationJournal of Physics: Conference Series
DOIs
Publication statusPublished - 5 Dec 2018

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