{"title":"基于多智能体自适应模糊神经网络的电池光伏系统尺寸确定","authors":"E. Engel","doi":"10.1109/ENT.2016.019","DOIUrl":null,"url":null,"abstract":"This paper presents a method for modeling, sizing and cost analysis of a photovoltaic system with battery on the basis of the multi-agent adaptive fuzzy neuronet. The goal of this research is to find the best configuration of the system and the optimal sizing coefficient of a photovoltaic system on the basis of the multi-agent adaptive fuzzy neuronet. The simulation results show that the effectiveness of the proposed method is better than the genetic algorithm in sizing of a photovoltaic system with battery.","PeriodicalId":356690,"journal":{"name":"2016 International Conference on Engineering and Telecommunication (EnT)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":"{\"title\":\"Sizing of a Photovoltaic System with Battery on the Basis of the Multi-Agent Adaptive Fuzzy Neuronet\",\"authors\":\"E. Engel\",\"doi\":\"10.1109/ENT.2016.019\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents a method for modeling, sizing and cost analysis of a photovoltaic system with battery on the basis of the multi-agent adaptive fuzzy neuronet. The goal of this research is to find the best configuration of the system and the optimal sizing coefficient of a photovoltaic system on the basis of the multi-agent adaptive fuzzy neuronet. The simulation results show that the effectiveness of the proposed method is better than the genetic algorithm in sizing of a photovoltaic system with battery.\",\"PeriodicalId\":356690,\"journal\":{\"name\":\"2016 International Conference on Engineering and Telecommunication (EnT)\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-11-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"5\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 International Conference on Engineering and Telecommunication (EnT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ENT.2016.019\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 International Conference on Engineering and Telecommunication (EnT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ENT.2016.019","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sizing of a Photovoltaic System with Battery on the Basis of the Multi-Agent Adaptive Fuzzy Neuronet
This paper presents a method for modeling, sizing and cost analysis of a photovoltaic system with battery on the basis of the multi-agent adaptive fuzzy neuronet. The goal of this research is to find the best configuration of the system and the optimal sizing coefficient of a photovoltaic system on the basis of the multi-agent adaptive fuzzy neuronet. The simulation results show that the effectiveness of the proposed method is better than the genetic algorithm in sizing of a photovoltaic system with battery.
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