Hybrid energy generation for industrial application

Renewable energy is best solution for fulfill electricity demand but the conversion of system and load demand to be supplied are fluctuating and therefore it is even more difficult to predict the load and supply together. In this research project we had tried to develop criterion to improve the system size with lower cost and lower Cost of Energy (COE) by using Genetic Algorithm (GA) permutation and combination technique. Firstly make a simulation models to predict sizing and expenditure on hybrid renewable energy systems by using surface climate data (solar irradiance, wind speed etc.) of the particular area and the demand of electricity to particular facility. Once model is developed then it used to simulate and optimize the size of the hybrid renewable energy system which is best suited. The developed model also applied on hybrid system in validation case studies. The results from optimization are also validates on HOMER. Key words: Hybrid system, Simulation, Optimization, Cost of Energy (COE)

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