Abstract
Energy conversion and distribution is one of the drastically growing and leading research nowadays. Renewable energy systems are incorporated into the Grid system to fulfill the demand dispatch effectively. Various earlier approaches are used for scheduling the energy system incorporated into the grid, but the efficiency of the energy scheduling needs to be improved. The main aim of this paper is to reduce the operation cost using Grey Wolf Optimization (GWO) algorithm for providing an efficient solution for energy scheduling problems in the hybrid energy microgrid system. The hybrid energy system comprises of solar, wind, thermal and electrical vehicles, and analyzed by conducting a simulation. It is found that the proposed GWO model is efficient and represent that this algorithm has a better global search ability than the exiting PSO and MPSO approach.
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Shilaja, C. (2021). A Meta-heuristic Optimization Algorithm for Solving Renewable Energy System. In: Borah, S., Pradhan, R., Dey, N., Gupta, P. (eds) Soft Computing Techniques and Applications. Advances in Intelligent Systems and Computing, vol 1248. Springer, Singapore. https://doi.org/10.1007/978-981-15-7394-1_42
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DOI: https://doi.org/10.1007/978-981-15-7394-1_42
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