Soft Computing

, Volume 23, Issue 21, pp 10811–10820 | Cite as

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

  • Tejeswara Rao Nartu
  • Mani Sankar MattaEmail author
  • Sravani Koratana
  • Ravi Kumar Bodda
Methodologies and Application


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.


Power loss minimization Multiobjective cuckoo search algorithm Pareto-optimal solution Optimal location Static VAR compensator 


Compliance with ethical standards

Conflict of interest

All the authors do not have any conflict of interest.

Human and animal rights statement

This article does not contain any studies with human participants or animals performed by any of the authors.


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Department of Electrical and Electronics EngineeringAditya Institute of Technology and ManagementTekkaliIndia
  2. 2.Department of Electrical EngineeringBIT SindriDhanbadIndia

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