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• W2024009628 abstract "Along with the increasing demand for electrical power, distributed generations (DGs) have so far found their pivotal roles in the restructured environment of power distribution systems. As an indispensable step toward a more reliable power system, the DGs optimal allocation strategy, deemed to be the most techno-economically efficient scheme, comes to the play and is profoundly taken under concentration in this study. This paper devises a comprehensive multi-objective (MO) optimization approach by which all the crucial and maybe contradictory aspects of great influence in the placement process can be accounted for. Total imposed costs, total network losses, customer outage costs as well as absorbed private investments are those considered objectives in the proposed scheme. Non-dominated Sorting Genetic Algorithm II (NSGAII), as a robust widely-used method of multi-objective dilemmas, is employed to cope with the optimization problem. Point Estimation Method (PEM) has also lent the authors a hand in probabilistically approaching the involved uncertain criteria. In the light of the proposed methodology being implemented on the 37-Bus IEEE standard test system, the anticipated efficiency of the proposed method is well verified." @default.
• W2024009628 created "2016-06-24" @default.
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• W2024009628 date "2013-10-01" @default.
• W2024009628 modified "2023-09-24" @default.
• W2024009628 title "Optimal siting of DG units in power systems from a probabilistic multi-objective optimization perspective" @default.
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• W2024009628 doi "https://doi.org/10.1016/j.ijepes.2013.02.014" @default.
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