Abstract
In this paper we have studied the power management for residential area. A proper load management brought fruitful results in term of Peak to Average Ratio (PAR) reduction and electricity cost. In order to achieve these objectives, we provide an energy management structure to perform scheduling on the basis of Genetic Algorithm (GA) and Fish Swarm Optimization (FSO). Time Of Use (TOU) pricing scheme has been used to calculate electricity cost. After experiments a noticeable difference has been found in the performance of our proposed algorithms GA and FSO. GA provides us better results in term of energy consumption and PAR reduction as compared to FSO. However, FSO performs more efficiently than GA in term of electricity cost reduction.
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Saeed, M.S. et al. (2018). Power Management in Smart Grid for Residential Consumers. In: Xhafa, F., Caballé, S., Barolli, L. (eds) Advances on P2P, Parallel, Grid, Cloud and Internet Computing. 3PGCIC 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 13. Springer, Cham. https://doi.org/10.1007/978-3-319-69835-9_39
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DOI: https://doi.org/10.1007/978-3-319-69835-9_39
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