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Soft Computing
Published in: Soft Computing 21/2019

17-11-2018 | Methodologies and Application

A fuzzified Pareto multiobjective cuckoo search algorithm for power losses minimization incorporating SVC

Authors: Tejeswara Rao Nartu, Mani Sankar Matta, Sravani Koratana, Ravi Kumar Bodda

Published in: Soft Computing | Issue 21/2019

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Abstract

This paper presents an application of multiobjective cuckoo search (MOCS) algorithm for reduction in transmission line losses by placing static VAR compensator (SVC) at an optimal location. MOCS algorithm is an extension of the infamous cuckoo search algorithm. The multiobjective optimizations considered in this paper include active power loss and reactive power loss, active power loss and investment cost of SVC. The Pareto-optimal solution which is obtained by using the Pareto-optimal method gives the solution to the multiobjective problem. The fuzzy logic approach is used to obtain best trade-off solutions from the Pareto-optimal solution. A standard IEEE 30 bus test system is considered for testing the efficacy of the proposed methodology. The results show that installation of SVC and application of MOCS algorithm is effective in power loss reduction.
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Metadata
Title
A fuzzified Pareto multiobjective cuckoo search algorithm for power losses minimization incorporating SVC
Authors
Tejeswara Rao Nartu
Mani Sankar Matta
Sravani Koratana
Ravi Kumar Bodda
Publication date
17-11-2018
Publisher
Springer Berlin Heidelberg
Published in
Soft Computing / Issue 21/2019
Print ISSN: 1432-7643
Electronic ISSN: 1433-7479
DOI
https://doi.org/10.1007/s00500-018-3634-7

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