Ant Lion Optimization Algorithm for optimal location and sizing of renewable distributed generations

E.S. Ali, S.M. Abd Elazim and A.Y. Abdelaziz

Renewable Energy, 2017, vol. 101, issue C, 1311-1324

Abstract: Renewable sources can supply a clean and smart solution to the increased demands. Thus, Photovoltaic (PV) and Wind Turbine (WT) are taken here as resources of Distributed Generation (DG). Location and sizing of DG have affected largely on the system losses. In this paper, Ant Lion Optimization Algorithm (ALOA) is proposed for optimal location and sizing of DG based renewable sources for various distribution systems. First the most candidate buses for installing DG are introduced using Loss Sensitivity Factors (LSFs). Then the proposed ALOA is used to deduce the locations and sizing of DG from the elected buses. The proposed algorithm is tested on two IEEE radial distribution systems. The obtained results via the proposed algorithm are compared with other algorithms to highlight its benefits in decreasing total power losses and consequently increasing the net saving. Moreover, the results are presented to confirm the effectiveness of ALOA in enhancing the voltage profiles for different distribution systems and loading conditions. Also, the Wilcoxon test is performed to verify the superiority of ALOA.

Keywords: Distributed generation; Renewable energy; Loss reduction; Voltage profiles; Ant lion optimization algorithm; Loss sensitivity factors (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (27)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:renene:v:101:y:2017:i:c:p:1311-1324

DOI: 10.1016/j.renene.2016.09.023

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