EFFICIENT SOLAR ENERGY HARVESTING USING IMAGE PROCESSING AND SOFT COMPUTING TECHNIQUE

Abstract

Electricity is a vital power source for the world's rapidly rising population, and its usage of conventional resources is hazardous to the world environs. This cause is related to the destruction of the atmosphere and environs, so effective decision is essential to overcome these challenges, which resulted in the rapid development of sustainable. Geothermal, Hydropower, Solar, Biofuels & wind energy are the main renewable resources with contributed to the development of our country and their market have been growing at rapid pace since the Indian government introduce different economic policies to reduce the generation of greenhouse gasses. Beyond this renewable energy, solar energy is most favourable energy regarding India where on average 245 days of clear sky out of 365 days. Sun energy is gaining popularity and is poised to be among the most essential components of the future of the planet power harvesting and financial growth. The use of low-cost, energy efficient solar power systems is one strategy to upsurge the usage of Sun power schemes, particularly in rural and underdeveloped areas. There are various types of solar power system to extract electricity or heat energy. This report dispenses the design, working and result analysis of a two-axis soft computing and GPS based solar energy harvesting system. This Nobel method improved result compare to various solar power extractors like, Stable panel system, one axis LDR centred Sun tracer, two axis LDR centred Sun tracer. The above said Sun energy extractor system have various draw back which is remove in applied system. LDR sensor based sun followers have low tracking accuracy and because of an electrical part low sensitivity to climate and can damage by lightning discharge, It works on the sensor so its tracker is obstructed which produce hampers in energy production and System require continuously monitored. We have also simulated the hybrid system and performance parameter is evaluated.