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W4386213663 abstract "The primary objective of this research is to identify the optimal size of various energy supplies to satisfy demand at the reduced possible cost and with the highest possible dependability. For this objective, two distinct modes of operation are considered: Wind/PV/battery and Wind/PV/battery/EV. After tuning the arrangement and identifying the optimum amount of components and cost at various degrees of dependability by the proposed algorithm in the first scenario, an EV with deterministic and stochastic behavior is introduced to the system in the second scenario, and the LPSP is computed in both modes. It has been demonstrated that EVs improve system dependability. By utilizing the suggested Adapti ve Dwarf Mongoose (Adap-DMO) algorithm, this research solves the novel optimum size challenge for HRESs with EVs to lower costs and increase system dependability. The Adap-DMO method suggested here is a swarm intelligence-based solution influenced by the behavior of the Dwarf mongoose that addresses the limitations of the standard DMO algorithm. Furthermore, Matlab/Simulink is used to predict the uncertainties associated with the EVs, which include the timings of arrival and departure as well as the arrival SOC of the EV. The findings revealed that both systems' designs are realistic; nevertheless, the first one was more effective compared to the second system as it utilized fewer wind units compared to the second one. Finally, the effect of raising and lowering wind speed and load demand by 10 % , 20 % , and 30% on decision factors was examined." @default.
W4386213663 created "2023-08-29" @default.
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W4386213663 date "2023-08-03" @default.
W4386213663 modified "2023-09-30" @default.
W4386213663 title "Optimal Sizing of Grid-Connected HRES with and Without EV using Adaptive-Dwarf Mongoose Optimization Technique" @default.
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W4386213663 doi "https://doi.org/10.1109/icirca57980.2023.10220895" @default.
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