José Almeida, Rafael Barbarroxa, F. Lezama, J. Soares, L. Gomes, F. Oliveira, Z. Vale
{"title":"Meta-ERM: Metaheuristic Optimization Platform for Energy Resource Management in the Smart Grid","authors":"José Almeida, Rafael Barbarroxa, F. Lezama, J. Soares, L. Gomes, F. Oliveira, Z. Vale","doi":"10.1109/CAI54212.2023.00034","DOIUrl":null,"url":null,"abstract":"The energy resource management problem is regarded with great importance in the energy domain due to the current transformation of the electrical grid as a result of the growth of smart grid technologies. In this situation, conventional formulations created for an entirely different scenario occasionally fail to address the issue effectively. Modern metaheuristic optimizers are a powerful tool for handling such issues when old techniques fail. This work proposes a user-friendly web Meta-ERM platform for metaheuristic optimization when solving a given case study’s energy resource management problem and allows the visualization of performance analysis.","PeriodicalId":129324,"journal":{"name":"2023 IEEE Conference on Artificial Intelligence (CAI)","volume":"57 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 IEEE Conference on Artificial Intelligence (CAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CAI54212.2023.00034","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
The energy resource management problem is regarded with great importance in the energy domain due to the current transformation of the electrical grid as a result of the growth of smart grid technologies. In this situation, conventional formulations created for an entirely different scenario occasionally fail to address the issue effectively. Modern metaheuristic optimizers are a powerful tool for handling such issues when old techniques fail. This work proposes a user-friendly web Meta-ERM platform for metaheuristic optimization when solving a given case study’s energy resource management problem and allows the visualization of performance analysis.