Real Power Loss Reduction by Revolutionary Algorithm

Dr.K.Lenin

Real Power Loss Reduction by Revolutionary Algorithm

Dr.K.Lenin * §

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Jawaharlal Nehru Technological University Kukatpally

Real Power Loss Reduction by Revolutionary Algorithm

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Abstract

In this paper, Kidney Search (KS) algorithm is proposed for solving reactive power problem. When using KS algorithm, solutions are rated based on the average value of the objective function in a particular population of particular round. Optimal solutions are identified in the filtered blood and the rest are considered as inferior solutions. As the algorithm proposed by the name of kidney, it reproduces various processes from the system of a biological kidney. Proposed Kidney search (KS) algorithm has been tested on standard IEEE 30 bus test system and simulation results show clearly about the better performance of the proposed KS algorithm in reducing the real power loss.

References

26 Cites in Article

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Funding

No external funding was declared for this work.

Conflict of Interest

The authors declare no conflict of interest.

Ethical Approval

No ethics committee approval was required for this article type.

Data Availability

Not applicable for this article.

How to Cite This Article

Dr.K.Lenin. 2017. "Real Power Loss Reduction by Revolutionary Algorithm". Global Journal of Research in Engineering - F: Electrical & Electronic GJRE-F Volume 17 (GJRE Volume 17 Issue F5).

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GJRE Volume 17 Issue F5

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Journal Specifications

Crossref Journal DOI 10.17406/gjre

Print ISSN 0975-5861

e-ISSN 2249-4596

Keywords

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Classification

GJRE-F Classification FOR Code: 090607

Submission ReceivedDecember 15, 2016
Peer Review Double Blind
Handling Editor
Accepted January 5, 2017
Published January 15, 2017

Version of record

v1.2

Issue date

October 2, 2017

Language

English

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Article Matrices

Total Score: 106

Country: India

Subject: Global Journal of Research in Engineering

Authors: Dr.K.Lenin (PhD/Dr. count: 1)

View Count (all-time): 350

Total Views (Real + Logic): 868

Total Downloads (simulated): 75

Publish Date: 2017 01, Sun

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Total Views: 868

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