{"title":"基于Maine Coon和Perognathinae优化算法的实际功率损耗降低","authors":"L. Kanagasabai, Prasad V. Potluri","doi":"10.18698/1812-3368-2023-3-61-84","DOIUrl":null,"url":null,"abstract":"This paper proposes Maine Coon and Perognathinae based optimization (MPO) algorithm for solving the power loss lessening problem. Usual behaviour between Maine Coon and Perognathinae is imitated to formulate the MPO algorithm. In the proposed MPO, the crusade of Maine Coon towards Perognathinae as well as the spurt of Perognathinae in the direction of anchorages is replicated. Proposed MPO is population-based procedure which is premeditated by imitating the natural actions of a Maine Coon assaults on Perognathinae and absconding of Perognathinae to the anchorage. The exploration agents in the projected MPO algorithm are alienated into two clusters of Maine Coon’s and Perognathinae that examine the problem exploration space with arbitrary activities. The projected MPO algorithm apprises population associates in two segments. In the principal segment, the crusade of Maine Coon’s in the direction of Perognathinae is modelled, and in the subsequent segment, the absconding behaviour of Perognathinae to anchorages to protect its life is designed. From a scientific fact of opinion, every associate of the populace is a recommended solution to the problem. In detail, an associate of the population postulates standards for the problem parameters rendering to its location in the exploration space. Proposed MPO algorithm is appraised in IEEE 30 bus system and IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage constancy index. True power loss lessening, voltage divergence curtailing, and voltage constancy index augmentation has been attained","PeriodicalId":12961,"journal":{"name":"Herald of the Bauman Moscow State Technical University. Series Natural Sciences","volume":"18 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Real Power Loss Reduction by Maine Coon and Perognathinae Based Optimization Algorithm\",\"authors\":\"L. Kanagasabai, Prasad V. Potluri\",\"doi\":\"10.18698/1812-3368-2023-3-61-84\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes Maine Coon and Perognathinae based optimization (MPO) algorithm for solving the power loss lessening problem. Usual behaviour between Maine Coon and Perognathinae is imitated to formulate the MPO algorithm. In the proposed MPO, the crusade of Maine Coon towards Perognathinae as well as the spurt of Perognathinae in the direction of anchorages is replicated. Proposed MPO is population-based procedure which is premeditated by imitating the natural actions of a Maine Coon assaults on Perognathinae and absconding of Perognathinae to the anchorage. The exploration agents in the projected MPO algorithm are alienated into two clusters of Maine Coon’s and Perognathinae that examine the problem exploration space with arbitrary activities. The projected MPO algorithm apprises population associates in two segments. In the principal segment, the crusade of Maine Coon’s in the direction of Perognathinae is modelled, and in the subsequent segment, the absconding behaviour of Perognathinae to anchorages to protect its life is designed. From a scientific fact of opinion, every associate of the populace is a recommended solution to the problem. In detail, an associate of the population postulates standards for the problem parameters rendering to its location in the exploration space. Proposed MPO algorithm is appraised in IEEE 30 bus system and IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage constancy index. True power loss lessening, voltage divergence curtailing, and voltage constancy index augmentation has been attained\",\"PeriodicalId\":12961,\"journal\":{\"name\":\"Herald of the Bauman Moscow State Technical University. Series Natural Sciences\",\"volume\":\"18 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Herald of the Bauman Moscow State Technical University. 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Real Power Loss Reduction by Maine Coon and Perognathinae Based Optimization Algorithm
This paper proposes Maine Coon and Perognathinae based optimization (MPO) algorithm for solving the power loss lessening problem. Usual behaviour between Maine Coon and Perognathinae is imitated to formulate the MPO algorithm. In the proposed MPO, the crusade of Maine Coon towards Perognathinae as well as the spurt of Perognathinae in the direction of anchorages is replicated. Proposed MPO is population-based procedure which is premeditated by imitating the natural actions of a Maine Coon assaults on Perognathinae and absconding of Perognathinae to the anchorage. The exploration agents in the projected MPO algorithm are alienated into two clusters of Maine Coon’s and Perognathinae that examine the problem exploration space with arbitrary activities. The projected MPO algorithm apprises population associates in two segments. In the principal segment, the crusade of Maine Coon’s in the direction of Perognathinae is modelled, and in the subsequent segment, the absconding behaviour of Perognathinae to anchorages to protect its life is designed. From a scientific fact of opinion, every associate of the populace is a recommended solution to the problem. In detail, an associate of the population postulates standards for the problem parameters rendering to its location in the exploration space. Proposed MPO algorithm is appraised in IEEE 30 bus system and IEEE 14, 30, 57, 118, 300 bus test systems without considering the voltage constancy index. True power loss lessening, voltage divergence curtailing, and voltage constancy index augmentation has been attained
期刊介绍:
The journal is aimed at publishing most significant results of fundamental and applied studies and developments performed at research and industrial institutions in the following trends (ASJC code): 2600 Mathematics 2200 Engineering 3100 Physics and Astronomy 1600 Chemistry 1700 Computer Science.