ECONOMICALLY OPTIMAL DESIGN OF HYBRID RENEWABLE ENERGY SYSTEMS USING HOMER AND ACO

Today, the growing energy demand has shaped dramatic depletion of fossil fuels and unavoidable rising energy values. Furthermore, environmental effect of fossil fuel led to vital for using Renewable Energy (RE) to meet the increasing energy demand and resolve the emission problems. Irregularity and the high price of the renewable energy technologies are the key challenges of renewable energy usage. This approach presents an arranged examination for optimum pattern of Hybrid Renewable Energy Systems (HRES). The optimization was appreciated through the usage of Hybrid Optimization Model for Electric Renewable (HOMER) program and Ant colony optimization (ACO) algorithms in MATLAB is existing in this study. The recommended methodology has been proven on an incident study of an HRES that includes wind turbine, photovoltaic (PV) panels, natural gas generator and batteries. In conclusion, HRES design via a multi-impartial optimization source. The main purpose of the design is to promptly reduce total Net Present Cost (NPC), maximize renewable energy quotient, and decrease fuel emission.
Additionally ACO algorithms not common usage in similar renewable energy studies which give advantage and make this study pioneer in this field, Also give more accurate results compared with HOMER program that shows in this paper.