{"title":"Optimization of biomass waste gasification Combined Heat and Power System","authors":"B. Fakhimghanbarzadeh, H. Marzi, H. Abolghasem","doi":"10.1109/EPEC.2010.5697239","DOIUrl":null,"url":null,"abstract":"The objective of the research done in this paper was to determine cost of the power and heat system with pressurized fluidized bed gasifier using exergoexonomic appraisal techniques. Exergetic efficiency maximization was approached with use of multi-objective evolutionary optimization methods which were designed such that the costs were minimized in line with the exergoeconomic plans. The results of this method were also compared to methods that employ iterative techniques. Results showed an almost 12.28% improvement in exergetic efficient that the system could reach through utilization of the multi-objective evolutionary algorithm.","PeriodicalId":393869,"journal":{"name":"2010 IEEE Electrical Power & Energy Conference","volume":"41 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2010-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"4","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 IEEE Electrical Power & Energy Conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EPEC.2010.5697239","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 4
Abstract
The objective of the research done in this paper was to determine cost of the power and heat system with pressurized fluidized bed gasifier using exergoexonomic appraisal techniques. Exergetic efficiency maximization was approached with use of multi-objective evolutionary optimization methods which were designed such that the costs were minimized in line with the exergoeconomic plans. The results of this method were also compared to methods that employ iterative techniques. Results showed an almost 12.28% improvement in exergetic efficient that the system could reach through utilization of the multi-objective evolutionary algorithm.