Priyanka Brahamne, Assoc. Prof. M. P. S. Chawla, Dr. H. K. Verma
{"title":"Optimal Sizing of Hybrid Renewable Energy System using Manta Ray Foraging Technique","authors":"Priyanka Brahamne, Assoc. Prof. M. P. S. Chawla, Dr. H. K. Verma","doi":"10.35940/ijese.c2545.0211323","DOIUrl":null,"url":null,"abstract":"In this paper, a method for optimizing the size of a standalone hybrid that consists of a wind, PV, and biomass energy system with battery storage is discussed. Hybrid renewable energy systems are required in off-the-grid communities. For such systems, the optimal system sizing can be regarded as one of the constrained optimization issues. This research presents an intelligent approach based on modern optimization for designing the hybrid renewable energy system optimally using the manta ray foraging technique, minimizing overall annualized system cost and satisfying load demand. In order to confirm the effectiveness of the proposed method, results are compared against findings from the ABC algorithm. The results have proven that the MRFO algorithm has fast convergence properties, the ability to deliver high-quality results, and the capacity to manage a smooth power flow under the same ideal conditions.","PeriodicalId":275796,"journal":{"name":"International Journal of Emerging Science and Engineering","volume":"23 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-02-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Emerging Science and Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35940/ijese.c2545.0211323","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
In this paper, a method for optimizing the size of a standalone hybrid that consists of a wind, PV, and biomass energy system with battery storage is discussed. Hybrid renewable energy systems are required in off-the-grid communities. For such systems, the optimal system sizing can be regarded as one of the constrained optimization issues. This research presents an intelligent approach based on modern optimization for designing the hybrid renewable energy system optimally using the manta ray foraging technique, minimizing overall annualized system cost and satisfying load demand. In order to confirm the effectiveness of the proposed method, results are compared against findings from the ABC algorithm. The results have proven that the MRFO algorithm has fast convergence properties, the ability to deliver high-quality results, and the capacity to manage a smooth power flow under the same ideal conditions.