{"title":"基于atc问题的太阳风-热液调度多目标混沌混沌优化","authors":"Kingsuk Majumdar, P. Roy, Subrata Banerjee","doi":"10.2316/j.2022.203-0382","DOIUrl":null,"url":null,"abstract":"The electrical power generation from conventional thermal power plants needs to be interconnected with natural resources like solar, wind, hydro units with all-day planning and operation strategies to save mother nature and meet the current electricity demand. The complexity and size of the power network are increasing rapidly day by day. The enhanced power transfer from one section to another section in the existing grid system is the subject of available transfer capability (ATC), which is the modern power system’s critical factor. In this paper, the minimization of power generation cost of the thermal power units is achieved by incorporating renewable sources, says hydro, winds, and solar plants for 24 h scheduled, and ATC calculation is the prime objective. In recent literature, the Mayfly algorithm (MA) optimization approach, which combines the advantages of evolutionary algorithms and swarms intelligence to attend better results, is successfully implemented. In this article, optimum power flow-based ATC is enforced under various conditions with hydro-thermal-solar-wind scheduling concept on the IEEE 9 test bus system to check the performance of the proposed chaotic MA. The chaotic MA is a hybridized format of the MA and chaotic map (CHMA) method. It is noted from the simulation study that the suggested CHMA approach has a dominant nature over other well-established optimization algorithms. In case of single objective function, the value of the cost function is improved by 14% and that of for multi-objective, it is improved by more than 20% and ATC value is enhanced by near about 55% and more.","PeriodicalId":43153,"journal":{"name":"International Journal of Power and Energy Systems","volume":"66 1","pages":""},"PeriodicalIF":0.3000,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"MULTI-OBJECTIVE CHAOTIC MAYFLY OPTIMIZATION FOR SOLAR-WIND-HYDROTHERMAL SCHEDULING BASED ON ATC PROBLEM\",\"authors\":\"Kingsuk Majumdar, P. Roy, Subrata Banerjee\",\"doi\":\"10.2316/j.2022.203-0382\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The electrical power generation from conventional thermal power plants needs to be interconnected with natural resources like solar, wind, hydro units with all-day planning and operation strategies to save mother nature and meet the current electricity demand. The complexity and size of the power network are increasing rapidly day by day. The enhanced power transfer from one section to another section in the existing grid system is the subject of available transfer capability (ATC), which is the modern power system’s critical factor. In this paper, the minimization of power generation cost of the thermal power units is achieved by incorporating renewable sources, says hydro, winds, and solar plants for 24 h scheduled, and ATC calculation is the prime objective. In recent literature, the Mayfly algorithm (MA) optimization approach, which combines the advantages of evolutionary algorithms and swarms intelligence to attend better results, is successfully implemented. In this article, optimum power flow-based ATC is enforced under various conditions with hydro-thermal-solar-wind scheduling concept on the IEEE 9 test bus system to check the performance of the proposed chaotic MA. The chaotic MA is a hybridized format of the MA and chaotic map (CHMA) method. It is noted from the simulation study that the suggested CHMA approach has a dominant nature over other well-established optimization algorithms. In case of single objective function, the value of the cost function is improved by 14% and that of for multi-objective, it is improved by more than 20% and ATC value is enhanced by near about 55% and more.\",\"PeriodicalId\":43153,\"journal\":{\"name\":\"International Journal of Power and Energy Systems\",\"volume\":\"66 1\",\"pages\":\"\"},\"PeriodicalIF\":0.3000,\"publicationDate\":\"2022-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Power and Energy Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.2316/j.2022.203-0382\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"ENGINEERING, ELECTRICAL & ELECTRONIC\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Power and Energy Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2316/j.2022.203-0382","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"ENGINEERING, ELECTRICAL & ELECTRONIC","Score":null,"Total":0}
MULTI-OBJECTIVE CHAOTIC MAYFLY OPTIMIZATION FOR SOLAR-WIND-HYDROTHERMAL SCHEDULING BASED ON ATC PROBLEM
The electrical power generation from conventional thermal power plants needs to be interconnected with natural resources like solar, wind, hydro units with all-day planning and operation strategies to save mother nature and meet the current electricity demand. The complexity and size of the power network are increasing rapidly day by day. The enhanced power transfer from one section to another section in the existing grid system is the subject of available transfer capability (ATC), which is the modern power system’s critical factor. In this paper, the minimization of power generation cost of the thermal power units is achieved by incorporating renewable sources, says hydro, winds, and solar plants for 24 h scheduled, and ATC calculation is the prime objective. In recent literature, the Mayfly algorithm (MA) optimization approach, which combines the advantages of evolutionary algorithms and swarms intelligence to attend better results, is successfully implemented. In this article, optimum power flow-based ATC is enforced under various conditions with hydro-thermal-solar-wind scheduling concept on the IEEE 9 test bus system to check the performance of the proposed chaotic MA. The chaotic MA is a hybridized format of the MA and chaotic map (CHMA) method. It is noted from the simulation study that the suggested CHMA approach has a dominant nature over other well-established optimization algorithms. In case of single objective function, the value of the cost function is improved by 14% and that of for multi-objective, it is improved by more than 20% and ATC value is enhanced by near about 55% and more.
期刊介绍:
First published in 1972, this journal serves a worldwide readership of power and energy professionals. As one of the premier referred publications in the field, this journal strives to be the first to explore emerging energy issues, featuring only papers of the highest scientific merit. The subject areas of this journal include power transmission, distribution and generation, electric power quality, education, energy development, competition and regulation, power electronics, communication, electric machinery, power engineering systems, protection, reliability and security, energy management systems and supervisory control, economics, dispatching and scheduling, energy systems modelling and simulation, alternative energy sources, policy and planning.