Abstract
The electrical energy requirement is increasing day by day as many of the mechanical systems like motor vehicles and industrial engines are compensated with electrical equipment due to its environment friendly nature. However, most of the design of electrical power generation units do not seem to be eco-friendly as that of the electrical motors and drives. Therefore, the concentration has moved towards the non-renewable energy generation possibilities. Power stations that are operated by wind, solar and hydro stations attract the developers due to their minimum maintenance cost and higher operational efficiency. Hence, the combinations of two or three renewable energy sources are clubbed in many places to form a Distributed Generation (DG) setup. Such DG system requires an efficient switching operation for managing the power outcome from different generating stations to meet the load requirement. To meetup such requirement, a combination of Genetic Algorithm (GA) with the Particle Swarm Optimization (PSO) based technique has been developed in this work. A simulated experiment is also conducted in the work to prove the efficiency of the proposed hybrid model over the traditional GA and PSO approaches.
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