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• W3124003092 abstract "This Paper presents an energy management strategy of a wind-solar hybrid system installed at a remote rural village for residential users based on a Modified Genetic Algorithm (MGA). In this stand-alone wind-PV system no grid connection is needed, therefore we developed a suitable load management control in order to ensure and satisfy the electric load demand. An energy audit has been established for a typical residential house, then a scheduled hourly load is defined to the 24 hours of the day; MGA was applied after that to optimise the load allocation in real time by taking into consideration the priority of the loads and the available energy for each hour. Therefore, provide a better energy management efficiency and guarantee the end-user satisfaction. The developed algorithm allows testing the ability of the proposed MGA under different scenarios to approve the proposed strategy. The results have shown a good performance of the proposed algorithm to meet the aim of being efficient to use to any load profile. The different data used in this paper are taken from a work of Ibadan University, Nigeria [Ogunjuyigbe, A. S. O., T. R. Ayodele, and C. G. Monyei. 2015. “An Intelligent Load Manager for PV Powered Off-grid Residential Houses.” Energy for Sustainable Development 26: 34–42. doi:10.1016/j.esd] from which this current work was inspired." @default.
• W3124003092 created "2021-02-01" @default.
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• W3124003092 date "2021-01-25" @default.
• W3124003092 modified "2023-09-27" @default.
• W3124003092 title "Smart load management for a stand-alone wind-solar hybrid system" @default.
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• W3124003092 doi "https://doi.org/10.1080/01430750.2021.1875045" @default.
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