J. G. Hernández-Travieso, C. Travieso-González, J. B. Alonso, M. Dutta
{"title":"用于估算太阳能发电量的太阳辐射模型","authors":"J. G. Hernández-Travieso, C. Travieso-González, J. B. Alonso, M. Dutta","doi":"10.1109/IC3.2014.6897230","DOIUrl":null,"url":null,"abstract":"To know in advance the value of solar radiation is an advantage in order to obtain solar energy. This paper proposes the design and implementation of solar radiation modelling for the estimation of the solar energy generation, based on different series of data collected from meteorological stations in Gran Canaria and Tenerife (Canary Islands, Spain), helping to generate green energy from sun by the estimation of solar radiation. Artificial Neural Network multilayer perceptron, were the classification method used to obtain the forecast. The study of solar radiation prediction achieves a mean average error of 0.04 kilowatts hour per square meter.","PeriodicalId":444918,"journal":{"name":"2014 Seventh International Conference on Contemporary Computing (IC3)","volume":"234 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"7","resultStr":"{\"title\":\"Solar radiation modelling for the estimation of the solar energy generation\",\"authors\":\"J. G. Hernández-Travieso, C. Travieso-González, J. B. Alonso, M. Dutta\",\"doi\":\"10.1109/IC3.2014.6897230\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"To know in advance the value of solar radiation is an advantage in order to obtain solar energy. This paper proposes the design and implementation of solar radiation modelling for the estimation of the solar energy generation, based on different series of data collected from meteorological stations in Gran Canaria and Tenerife (Canary Islands, Spain), helping to generate green energy from sun by the estimation of solar radiation. Artificial Neural Network multilayer perceptron, were the classification method used to obtain the forecast. The study of solar radiation prediction achieves a mean average error of 0.04 kilowatts hour per square meter.\",\"PeriodicalId\":444918,\"journal\":{\"name\":\"2014 Seventh International Conference on Contemporary Computing (IC3)\",\"volume\":\"234 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"7\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2014 Seventh International Conference on Contemporary Computing (IC3)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/IC3.2014.6897230\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Seventh International Conference on Contemporary Computing (IC3)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3.2014.6897230","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Solar radiation modelling for the estimation of the solar energy generation
To know in advance the value of solar radiation is an advantage in order to obtain solar energy. This paper proposes the design and implementation of solar radiation modelling for the estimation of the solar energy generation, based on different series of data collected from meteorological stations in Gran Canaria and Tenerife (Canary Islands, Spain), helping to generate green energy from sun by the estimation of solar radiation. Artificial Neural Network multilayer perceptron, were the classification method used to obtain the forecast. The study of solar radiation prediction achieves a mean average error of 0.04 kilowatts hour per square meter.