Abstract
For residential consumers demand of energy is a main issue. To resolve this issue different techniques are being proposed. In this paper, our focus is on shifting the load from on-peak hours to off-peak hours to minimize peak to average ratio (PAR) and electricity cost. To fulfill these requirements, we adapt two heuristic algorithms, genetic algorithm (GA) and biogeography based optimization (BBO) algorithm. For energy pricing, we use real time pricing (RTP) scheme. Results demonstrate that the proposed algorithm minimize the PAR and electricity bill.
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Maroof, R., Khan, H.N., Ambreen, K., Iftikhar, H., Asif, S., Javaid, N. (2018). Residential Area Power Management Using Genetic Algorithm and Biogeography Based Optimization in Smart Grid. In: Barolli, L., Enokido, T., Takizawa, M. (eds) Advances in Network-Based Information Systems. NBiS 2017. Lecture Notes on Data Engineering and Communications Technologies, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-319-65521-5_68
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DOI: https://doi.org/10.1007/978-3-319-65521-5_68
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