{"title":"利用混合混沌自牧优化器和 24 小时可再生能源供热调度计算可用传输能力","authors":"Kingsuk Majumdar;Provas Kumar Roy;Subrata Banerjee","doi":"10.23919/CJEE.2023.000032","DOIUrl":null,"url":null,"abstract":"As fossil fuel stocks are being depleted, alternative sources of energy must be explored. Consequently, traditional thermal power plants must coexist with renewable resources, such as wind, solar, and hydro units, and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand. The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity (ATC) of current systems. Thermal units are linked to sources of renewable energy such as hydro, wind, and solar power, and are set up to run for 24 h. By contrast, new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos. Chaos seems to increase the performance and convergence properties of existing optimization approaches. In this study, selfish animal tendencies, mathematically represented as selfish herd optimizers, were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs, creating a multi-objective optimization problem. To evaluate the performance of the proposed hybridized optimization technique, an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions, that is, the renewable energy source-thermal scheduling concept, on IEEE 9-bus, IEEE 39-bus, and Indian Northern Region Power Grid 246-bus test systems. The findings show that the proposed technique outperforms existing well-established optimization strategies.","PeriodicalId":36428,"journal":{"name":"Chinese Journal of Electrical Engineering","volume":"9 4","pages":"54-72"},"PeriodicalIF":0.0000,"publicationDate":"2023-12-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10345655","citationCount":"0","resultStr":"{\"title\":\"Calculation of Available Transfer Capability Using Hybrid Chaotic Selfish Herd Optimizer and 24 Hours RES-thermal Scheduling\",\"authors\":\"Kingsuk Majumdar;Provas Kumar Roy;Subrata Banerjee\",\"doi\":\"10.23919/CJEE.2023.000032\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"As fossil fuel stocks are being depleted, alternative sources of energy must be explored. Consequently, traditional thermal power plants must coexist with renewable resources, such as wind, solar, and hydro units, and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand. The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity (ATC) of current systems. Thermal units are linked to sources of renewable energy such as hydro, wind, and solar power, and are set up to run for 24 h. By contrast, new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos. Chaos seems to increase the performance and convergence properties of existing optimization approaches. In this study, selfish animal tendencies, mathematically represented as selfish herd optimizers, were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs, creating a multi-objective optimization problem. To evaluate the performance of the proposed hybridized optimization technique, an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions, that is, the renewable energy source-thermal scheduling concept, on IEEE 9-bus, IEEE 39-bus, and Indian Northern Region Power Grid 246-bus test systems. The findings show that the proposed technique outperforms existing well-established optimization strategies.\",\"PeriodicalId\":36428,\"journal\":{\"name\":\"Chinese Journal of Electrical Engineering\",\"volume\":\"9 4\",\"pages\":\"54-72\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-12-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10345655\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Chinese Journal of Electrical Engineering\",\"FirstCategoryId\":\"1087\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10345655/\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"Engineering\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Chinese Journal of Electrical Engineering","FirstCategoryId":"1087","ListUrlMain":"https://ieeexplore.ieee.org/document/10345655/","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Engineering","Score":null,"Total":0}
Calculation of Available Transfer Capability Using Hybrid Chaotic Selfish Herd Optimizer and 24 Hours RES-thermal Scheduling
As fossil fuel stocks are being depleted, alternative sources of energy must be explored. Consequently, traditional thermal power plants must coexist with renewable resources, such as wind, solar, and hydro units, and all-day planning and operation techniques are necessary to safeguard nature while meeting the current demand. The fundamental components of contemporary power systems are the simultaneous decrease in generation costs and increase in the available transfer capacity (ATC) of current systems. Thermal units are linked to sources of renewable energy such as hydro, wind, and solar power, and are set up to run for 24 h. By contrast, new research reports that various chaotic maps are merged with various existing optimization methodologies to obtain better results than those without the inclusion of chaos. Chaos seems to increase the performance and convergence properties of existing optimization approaches. In this study, selfish animal tendencies, mathematically represented as selfish herd optimizers, were hybridized with chaotic phenomena and used to improve ATC and/or reduce generation costs, creating a multi-objective optimization problem. To evaluate the performance of the proposed hybridized optimization technique, an optimal power flow-based ATC was enforced under various hydro-thermal-solar-wind conditions, that is, the renewable energy source-thermal scheduling concept, on IEEE 9-bus, IEEE 39-bus, and Indian Northern Region Power Grid 246-bus test systems. The findings show that the proposed technique outperforms existing well-established optimization strategies.