Pub Date : 2023-01-01DOI: 10.1007/s00202-022-01709-y
G V Naga Lakshmi, A Jayalaxmi, Venkataramana Veeramsetty
The optimal location of distributed generation (DG) is a critical challenge for distribution firms in order to keep the distribution network running smoothly. The optimal placement of DG units is an optimization challenge in which the objective function is to maximize distribution firms' financial benefit owing to reduced active power losses and emissions in the network. Bus voltage limits and feeder thermal limits are considered as constraints. To overcome the problem of trapping the solution toward the local optimal point and to achieve strong local and global searching capabilities, a new hybrid Jaya-Red Deer optimizer is proposed as an optimization approach in this study to determine the best placement and size of distributed generating units. In the MATLAB environment, the suggested method is implemented on IEEE 15 and PG & E 69 bus distribution systems and validated with Red Deer Optimizer, Dragonfly Algorithm, Genetic Algorithm, Particle Swarm Optimization, Jaya Algorithm and Black Widow Optimizer. Based on the simulation results, distribution firms may operate their networks with the greatest financial advantage by properly positioning and sizing their DG units.
{"title":"Optimal placement of distributed generation based on DISCO's financial benefit with loss and emission reduction using hybrid Jaya-Red Deer optimizer.","authors":"G V Naga Lakshmi, A Jayalaxmi, Venkataramana Veeramsetty","doi":"10.1007/s00202-022-01709-y","DOIUrl":"https://doi.org/10.1007/s00202-022-01709-y","url":null,"abstract":"<p><p>The optimal location of distributed generation (DG) is a critical challenge for distribution firms in order to keep the distribution network running smoothly. The optimal placement of DG units is an optimization challenge in which the objective function is to maximize distribution firms' financial benefit owing to reduced active power losses and emissions in the network. Bus voltage limits and feeder thermal limits are considered as constraints. To overcome the problem of trapping the solution toward the local optimal point and to achieve strong local and global searching capabilities, a new hybrid Jaya-Red Deer optimizer is proposed as an optimization approach in this study to determine the best placement and size of distributed generating units. In the MATLAB environment, the suggested method is implemented on IEEE 15 and PG & E 69 bus distribution systems and validated with Red Deer Optimizer, Dragonfly Algorithm, Genetic Algorithm, Particle Swarm Optimization, Jaya Algorithm and Black Widow Optimizer. Based on the simulation results, distribution firms may operate their networks with the greatest financial advantage by properly positioning and sizing their DG units.</p>","PeriodicalId":72886,"journal":{"name":"Electrical engineering (Berlin, Germany)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9789517/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"9367251","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2022-01-01Epub Date: 2022-01-25DOI: 10.1007/s00202-021-01474-4
Helmut Pfützner, Georgi Shilyashki, Emanuel Huber
Magnetic energy loss P of soft magnetic laminations like SiFe sheets tends to be expressed through an integral over the power product H · dB/dt. Already in earlier papers, we stressed that distinctions are needed for the quantities H and B. However, they are not considered in practically consistent ways, in the so far literature. Here, we discuss these distinctions in closer ways, comparing loss determination by calculation and measurement, respectively. A physically consistent procedure is described for the determination of loss and magnetization power functions through measurement of bi-located quantities HS and BC (S surface, C cross section). On the other hand, it is concluded that corresponding quantitative calculations-based on co-located quantities H and B-are impeded by the high amount of technological parameters of modern steel products. For example, they result from chemical additions, and-in particular-also from specific technologies of rolling, annealing, coating or scribing.
{"title":"Calculated versus measured iron losses and instantaneous magnetization power functions of electrical steel.","authors":"Helmut Pfützner, Georgi Shilyashki, Emanuel Huber","doi":"10.1007/s00202-021-01474-4","DOIUrl":"https://doi.org/10.1007/s00202-021-01474-4","url":null,"abstract":"<p><p>Magnetic energy loss <i>P</i> of soft magnetic laminations like SiFe sheets tends to be expressed through an integral over the power product <i>H</i> · d<i>B</i>/d<i>t</i>. Already in earlier papers, we stressed that distinctions are needed for the quantities <i>H</i> and <i>B</i>. However, they are not considered in practically consistent ways, in the so far literature. Here, we discuss these distinctions in closer ways, comparing loss determination by calculation and measurement, respectively. A physically consistent procedure is described for the determination of loss and magnetization power functions through measurement of bi-located quantities <i>H</i> <sub>S</sub> and <i>B</i> <sub>C</sub> (S surface, C cross section). On the other hand, it is concluded that corresponding quantitative calculations-based on co-located quantities <i>H</i> and <i>B</i>-are impeded by the high amount of technological parameters of modern steel products. For example, they result from chemical additions, and-in particular-also from specific technologies of rolling, annealing, coating or scribing.</p>","PeriodicalId":72886,"journal":{"name":"Electrical engineering (Berlin, Germany)","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2022-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9358998/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"40413441","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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