Bikash Kumar Saw, Aashish Kumar Bohre, Jalpa Thakkar, M. Kolhe
{"title":"基于APSO和TLBO的SDG和DSTATCOM网络重构影响的技术经济和环境规划方法","authors":"Bikash Kumar Saw, Aashish Kumar Bohre, Jalpa Thakkar, M. Kolhe","doi":"10.13052/dgaej2156-3306.38510","DOIUrl":null,"url":null,"abstract":"A Multi Objective based Fitness Function (MOFF) is proposed for the optimum planning of multiple Solar Distributed Generation (SDG) and DSTATCOM with radial distribution network (RDN) reconfiguration impact for techno-economic and environmental benefit improvement. The Adaptive-Particle Swarm Optimization (APSO) and Teaching-Learning Based Optimization techniques (TLBO) are employed to accomplish this work. In the proposed MOFF, the Active Power Loss (APLoss), Reactive Power Loss (RPLoss), System Voltage Deviation (SVD), Fault-Current Level-of-Line (FCLLine), and System Service Reliability (SSR) are considered. The economic-benefit measures along with Environmental Emissions Components (EEC) impact have also been considered in light of various system costs such as Fixed Capital Recovery Cost (FCRCost), Energy Loss Cost (ELCost) and Energy Not Supplied Cost (ENSCost). The novelty in the MOFF is the simultaneous consideration of FCLLine with APLoss, RPLoss, SVD, and SSR along with EEC impact calculation. The IEEE 69 and 118 bus RDN is considered with three case studies to demonstrate the proposed methodology's usefulness. The result analysis reveals that better performances can be obtained based on the considered MOFF in terms of environment-friendly techno-economic perspective, consistency, convergence, and computation time using TLBO rather than APSO. ","PeriodicalId":11205,"journal":{"name":"Distributed Generation & Alternative Energy Journal","volume":"30 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-07-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Techno-Economic and Environmental Based Approach for Planning of SDG and DSTATCOM with Impact of Network Reconfiguration using APSO and TLBO\",\"authors\":\"Bikash Kumar Saw, Aashish Kumar Bohre, Jalpa Thakkar, M. Kolhe\",\"doi\":\"10.13052/dgaej2156-3306.38510\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A Multi Objective based Fitness Function (MOFF) is proposed for the optimum planning of multiple Solar Distributed Generation (SDG) and DSTATCOM with radial distribution network (RDN) reconfiguration impact for techno-economic and environmental benefit improvement. The Adaptive-Particle Swarm Optimization (APSO) and Teaching-Learning Based Optimization techniques (TLBO) are employed to accomplish this work. In the proposed MOFF, the Active Power Loss (APLoss), Reactive Power Loss (RPLoss), System Voltage Deviation (SVD), Fault-Current Level-of-Line (FCLLine), and System Service Reliability (SSR) are considered. The economic-benefit measures along with Environmental Emissions Components (EEC) impact have also been considered in light of various system costs such as Fixed Capital Recovery Cost (FCRCost), Energy Loss Cost (ELCost) and Energy Not Supplied Cost (ENSCost). The novelty in the MOFF is the simultaneous consideration of FCLLine with APLoss, RPLoss, SVD, and SSR along with EEC impact calculation. The IEEE 69 and 118 bus RDN is considered with three case studies to demonstrate the proposed methodology's usefulness. The result analysis reveals that better performances can be obtained based on the considered MOFF in terms of environment-friendly techno-economic perspective, consistency, convergence, and computation time using TLBO rather than APSO. \",\"PeriodicalId\":11205,\"journal\":{\"name\":\"Distributed Generation & Alternative Energy Journal\",\"volume\":\"30 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-07-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Distributed Generation & Alternative Energy Journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.13052/dgaej2156-3306.38510\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Distributed Generation & Alternative Energy Journal","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.13052/dgaej2156-3306.38510","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Techno-Economic and Environmental Based Approach for Planning of SDG and DSTATCOM with Impact of Network Reconfiguration using APSO and TLBO
A Multi Objective based Fitness Function (MOFF) is proposed for the optimum planning of multiple Solar Distributed Generation (SDG) and DSTATCOM with radial distribution network (RDN) reconfiguration impact for techno-economic and environmental benefit improvement. The Adaptive-Particle Swarm Optimization (APSO) and Teaching-Learning Based Optimization techniques (TLBO) are employed to accomplish this work. In the proposed MOFF, the Active Power Loss (APLoss), Reactive Power Loss (RPLoss), System Voltage Deviation (SVD), Fault-Current Level-of-Line (FCLLine), and System Service Reliability (SSR) are considered. The economic-benefit measures along with Environmental Emissions Components (EEC) impact have also been considered in light of various system costs such as Fixed Capital Recovery Cost (FCRCost), Energy Loss Cost (ELCost) and Energy Not Supplied Cost (ENSCost). The novelty in the MOFF is the simultaneous consideration of FCLLine with APLoss, RPLoss, SVD, and SSR along with EEC impact calculation. The IEEE 69 and 118 bus RDN is considered with three case studies to demonstrate the proposed methodology's usefulness. The result analysis reveals that better performances can be obtained based on the considered MOFF in terms of environment-friendly techno-economic perspective, consistency, convergence, and computation time using TLBO rather than APSO.