PROJECT TITLE :

Optimal Sizing of Hybrid System for Standlaone application using Genetic Algorithm

ABSTRACT:

This research provides a new method for optimum hybrid energy system modelling. The suggested approach is primarily based on wind speed and solar radiation meteorological data. Optimize the Hybrid Energy System by lowering the total cost, the cost of energy (COE), and the annualised system cost in order to make the system more cost-effective for household applications. The Genetic Algorithm is used to achieve the optimization. The input chromosomes for the algorithm are wind turbine capacity, PV array ratings, capacity and number of battery banks, rated power of the diesel generator, system initialization cost, and O&M cost. To formulate the optimization strategy, a MATLAB application is created.