A Comprehensive multi criteria model to rank Solar Power Plant Sites using soft computing techniques

Abstract

Every nation today depends on various forms of non-renewable sources of energy like oil, coal, petroleum and natural gas for their daily needs, developmental project or to support progressing economy. These fossil fuels are limited and will be exhausted soon. Renewable energy sources like solar, wind, and water are clean, unlimited, and economical. Therefore, its share of total energy consumption has been increasing rapidly in the present scenario.  As selecting a site of SPP comprises of important factor like environment, local terrain and local weather issues, large investment in installing the plant becomes a serious matter. Multi-Criteria Decision Making (MCDM) is an approach that acknowledge one in choosing the best sites among proposed or available options.

Thus, this paper gives a detailed study of optimal ranking of SPP site using Analytical Hierarchy Process (AHP) and Multiple Layer Perceptron (MLP) neural network trained with Back Propagation (BP) algorithm. Three SPP sites of India were considered and various important criteria like local weather, geographical location, and environmental factors are included in our study as SPP site selection is a multi-criteria problem. AHP is a method depending on expert’s opinion to calculate the priority scales. It analyzes complex decision with the use of psychology and math’s. AHP is further compared to MLP-BP neural network for precise ranking of the site.