REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM

This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation...

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Main Author: Dr.K.Lenin
Format: Article in Journal/Newspaper
Language:unknown
Published: Zenodo 2017
Subjects:
Online Access:https://doi.org/10.5281/zenodo.583889
id ftzenodo:oai:zenodo.org:583889
record_format openpolar
spelling ftzenodo:oai:zenodo.org:583889 2024-09-15T18:00:03+00:00 REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM Dr.K.Lenin 2017-06-01 https://doi.org/10.5281/zenodo.583889 unknown Zenodo https://doi.org/10.5281/zenodo.601477 https://doi.org/10.5281/zenodo.583889 oai:zenodo.org:583889 info:eu-repo/semantics/openAccess Creative Commons Attribution 4.0 International https://creativecommons.org/licenses/by/4.0/legalcode INTERNATIONAL JOURNAL OF RESEARCH- GRANTHAALAYAH, 5(5), 88-98, (2017-06-01) Reactive Power Transmission Loss Mutual Mammal Behavior Optimization info:eu-repo/semantics/article 2017 ftzenodo https://doi.org/10.5281/zenodo.58388910.5281/zenodo.601477 2024-07-27T05:13:36Z This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. A Meta heuristic algorithm for global optimization called the Mutual Mammal Behavior (MM) is introduced. Mammal groups like Carnivores, African lion, Cheetah, Dingo Fennec Fox, Moose, Polar Bear, Sea Otter, Blue Whale, Bottlenose Dolphin exhibit a variety of behaviors including swarming about a food source, milling around a central location, or migrating over large distances in aligned groups. These Mutual behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency, to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, the searcher agents emulate a group of Mammals which interact with each other based on the biological laws of Mutual motion. MM powerful stochastic optimization technique has been utilized to solve the reactive power optimization problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 57,118 bus systems. Proposed MM algorithm out performs other reported standard algorithm’s in reducing real power loss. Article in Journal/Newspaper Blue whale Zenodo
institution Open Polar
collection Zenodo
op_collection_id ftzenodo
language unknown
topic Reactive Power
Transmission Loss
Mutual Mammal Behavior
Optimization
spellingShingle Reactive Power
Transmission Loss
Mutual Mammal Behavior
Optimization
Dr.K.Lenin
REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
topic_facet Reactive Power
Transmission Loss
Mutual Mammal Behavior
Optimization
description This paper presents a Mutual Mammal Behavior (MM) algorithm for solving Reactive power problem in power system. Modal analysis of the system is used for static voltage stability assessment. Loss minimization is taken is taken as main objective. Generator terminal voltages, reactive power generation of the capacitor banks and tap changing transformer setting are taken as the optimization variables. A Meta heuristic algorithm for global optimization called the Mutual Mammal Behavior (MM) is introduced. Mammal groups like Carnivores, African lion, Cheetah, Dingo Fennec Fox, Moose, Polar Bear, Sea Otter, Blue Whale, Bottlenose Dolphin exhibit a variety of behaviors including swarming about a food source, milling around a central location, or migrating over large distances in aligned groups. These Mutual behaviors are often advantageous to groups, allowing them to increase their harvesting efficiency, to follow better migration routes, to improve their aerodynamic, and to avoid predation. In the proposed algorithm, the searcher agents emulate a group of Mammals which interact with each other based on the biological laws of Mutual motion. MM powerful stochastic optimization technique has been utilized to solve the reactive power optimization problem. In order to evaluate up the performance of the proposed algorithm, it has been tested on Standard IEEE 57,118 bus systems. Proposed MM algorithm out performs other reported standard algorithm’s in reducing real power loss.
format Article in Journal/Newspaper
author Dr.K.Lenin
author_facet Dr.K.Lenin
author_sort Dr.K.Lenin
title REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
title_short REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
title_full REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
title_fullStr REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
title_full_unstemmed REAL POWER LOSS MINIMIZATION BY MUTUAL MAMMAL BEHAVIOR ALGORITHM
title_sort real power loss minimization by mutual mammal behavior algorithm
publisher Zenodo
publishDate 2017
url https://doi.org/10.5281/zenodo.583889
genre Blue whale
genre_facet Blue whale
op_source INTERNATIONAL JOURNAL OF RESEARCH- GRANTHAALAYAH, 5(5), 88-98, (2017-06-01)
op_relation https://doi.org/10.5281/zenodo.601477
https://doi.org/10.5281/zenodo.583889
oai:zenodo.org:583889
op_rights info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
op_doi https://doi.org/10.5281/zenodo.58388910.5281/zenodo.601477
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