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

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 Algor...

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Vydáno v:Renewable energy Ročník 101; s. 1311 - 1324
Hlavní autoři: Ali, E.S., Abd Elazim, S.M., Abdelaziz, A.Y.
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier Ltd 01.02.2017
Témata:
algorithms
Ant lion optimization algorithm
Distributed generation
Loss reduction
Loss sensitivity factors
Myrmeleontidae
Renewable energy
renewable energy sources
Voltage profiles
wind turbines
Loss reduction
Distributed generation
Ant lion optimization algorithm
Renewable energy
Loss sensitivity factors
Voltage profiles
ISSN:0960-1481, 1879-0682
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Shrnutí: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. •ALOA is proposed for optimal allocations and sizing of DG.•The objective function is designed to enhance system electrical performance.•The proposed algorithm is tested on various radial distribution systems.•The effectiveness of ALOA is verified compared with other algorithms.•The statistical assessment of ALOA is confirmed via Wilcoxon test.
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ISSN:0960-1481
1879-0682
DOI:10.1016/j.renene.2016.09.023