A Multi-criteria Decision-Making (MCDM) Approaches for Systematic Analysis and Ranking of Solar Power Plant Site Using ANN

Currently, environmental policies dedicated to adopting the progress, application, and performance of renewable energies (RES) are in focus. With the development of renewable energy sources, utilizing solar power has also become greater. Government of India (GOI) has also introduced various policies to promote diffusing of solar energy and has also invested a huge sum of money in the development of renewable energy. Because of this reason, choosing a suitable location for a solar farm power installation and getting the best radiation has become a very important agenda. Solar power plant site selection itself requires identifying and analyzing different multi-criteria such as environmental criteria, geographical criteria, economic criteria, and climatic criteria. The goal of the current work is to create a model that will help decision-makers rank or categorize different solar power plants sites in India using multiple criteria attributes applying artificial neural network (ANN) such as multiple layer perceptron (MLP) back-propagation (BP) and genetic algorithm (GA). This work shows a decisive effect, careful use of resources, and systematic decision support framework that will help the future policy planner throughout the review process for choosing an appropriate solar farm site in different states of India.