Optimization of aRE-based Microgrid using Genetic Algorithm in the perspective of Bangladesh

Renewable energy (RE) technologies are growing to be cost-effective and environmentally friendly ways to produce electricity. Day after day, more residents are becoming aware of the benefits of using RE-based microgrid networks to provide electricity to disengaged areas. Bangladesh, a densely populated country of the world, is still facing acute load shedding problems in its different regions, and aRE-based microgrid can be an efficient means to solve such kinds of problem. To set up a microgrid system, optimization is required for cost and reliability analysis. Genetic Algorithm (GA) is one of the most trending optimization techniques. Considering energy crisis of Bangladesh, in this paper, a RE-based microgrid is designed, and optimized using a novel genetic algorithm for ensuring minimum cost and greenhouse gas emissions. Here., GA optimization technique is implemented in Matlab 2015a environment, and optimal equipment capacity and operation planning is obtained. The optimization results show that the proposed microgrid system reduces the cost considerably, and reduces the emission of CO
2
99.56% with respect to the conventional fossil fuel-based system. Therefore, the proposed microgrid can be an effective energy solution for the rural areas of Bangladesh.