{"title":"基于先进灰狼优化算法的热液系统调度","authors":"Soudamini Behera, Ajit Kumar Barisal","doi":"10.1109/iSSSC56467.2022.10051309","DOIUrl":null,"url":null,"abstract":"In this paper Hydrothermal Scheduling (HTS) problems is solved using an advance Grey Wolf Optimizer algorithm named as Quasi Oppositional Grey Wolf Optimization (QOGWO) algorithm through cascaded reservoirs. Instead of pseudo-random numbers quasi-opposite numbers are used to initialize population in the proposed QOGWO method so that the convergence rate of GWO increases. Three intelligent algorithms such as GWO, QOGWO and Social network search (SNS)are compared in this complex hydrothermal system with many constraints. The feasibility of the projected approach is demonstrated in a multi-chain cascaded hydrothermal system with four interconnected hydro systems. Water transportation delay between interconnected reservoirs, Prohibited Discharge Zones (PDZ), Valve Point Loading (VPL) are considered in different combination in three cases. The PDZs of reservoirs of hydro plants have taken into account to ensure the viability of the projected method. The scheduled hourly rates of water flow founded by the projected QOGWO. The technique put forth with established superior to many recent findings for the STHS problems with increased complexities.","PeriodicalId":334645,"journal":{"name":"2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)","volume":"47 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-12-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Scheduling of HydroThermal System using Advance Grey Wolf Optimizer algorithm\",\"authors\":\"Soudamini Behera, Ajit Kumar Barisal\",\"doi\":\"10.1109/iSSSC56467.2022.10051309\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper Hydrothermal Scheduling (HTS) problems is solved using an advance Grey Wolf Optimizer algorithm named as Quasi Oppositional Grey Wolf Optimization (QOGWO) algorithm through cascaded reservoirs. Instead of pseudo-random numbers quasi-opposite numbers are used to initialize population in the proposed QOGWO method so that the convergence rate of GWO increases. Three intelligent algorithms such as GWO, QOGWO and Social network search (SNS)are compared in this complex hydrothermal system with many constraints. The feasibility of the projected approach is demonstrated in a multi-chain cascaded hydrothermal system with four interconnected hydro systems. Water transportation delay between interconnected reservoirs, Prohibited Discharge Zones (PDZ), Valve Point Loading (VPL) are considered in different combination in three cases. The PDZs of reservoirs of hydro plants have taken into account to ensure the viability of the projected method. The scheduled hourly rates of water flow founded by the projected QOGWO. The technique put forth with established superior to many recent findings for the STHS problems with increased complexities.\",\"PeriodicalId\":334645,\"journal\":{\"name\":\"2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)\",\"volume\":\"47 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2022-12-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/iSSSC56467.2022.10051309\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 IEEE 2nd International Symposium on Sustainable Energy, Signal Processing and Cyber Security (iSSSC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/iSSSC56467.2022.10051309","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Scheduling of HydroThermal System using Advance Grey Wolf Optimizer algorithm
In this paper Hydrothermal Scheduling (HTS) problems is solved using an advance Grey Wolf Optimizer algorithm named as Quasi Oppositional Grey Wolf Optimization (QOGWO) algorithm through cascaded reservoirs. Instead of pseudo-random numbers quasi-opposite numbers are used to initialize population in the proposed QOGWO method so that the convergence rate of GWO increases. Three intelligent algorithms such as GWO, QOGWO and Social network search (SNS)are compared in this complex hydrothermal system with many constraints. The feasibility of the projected approach is demonstrated in a multi-chain cascaded hydrothermal system with four interconnected hydro systems. Water transportation delay between interconnected reservoirs, Prohibited Discharge Zones (PDZ), Valve Point Loading (VPL) are considered in different combination in three cases. The PDZs of reservoirs of hydro plants have taken into account to ensure the viability of the projected method. The scheduled hourly rates of water flow founded by the projected QOGWO. The technique put forth with established superior to many recent findings for the STHS problems with increased complexities.