Gerardo Marcos Tornez-Xavier, F. Gómez-Castañeda, J. Moreno-Cadenas, L. M. Flores-Nava
{"title":"一个太阳能板仿真器的开发与实现","authors":"Gerardo Marcos Tornez-Xavier, F. Gómez-Castañeda, J. Moreno-Cadenas, L. M. Flores-Nava","doi":"10.1109/ICEEE.2013.6676052","DOIUrl":null,"url":null,"abstract":"This work describes the development and FPGA implementation of a solar panel emulator. First we created the electric analog model of the solar panel using the Mentor Graphics framework, using the irradiance and temperature variables of a meteorological database as input signals and then obtaining the short circuit current and the open circuit voltage parameters to finally train an artificial neural network using Matlab, to perform the modeling of the response of the solar panel. Once the neural network was optimized, this was described in VHDL to simulate its response, to finally make its implementation in FPGA digital device and to be able to compare these results with those of a commercial solar panel.","PeriodicalId":226547,"journal":{"name":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2013-12-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"14","resultStr":"{\"title\":\"FGPA development and implementation of a solar panel emulator\",\"authors\":\"Gerardo Marcos Tornez-Xavier, F. Gómez-Castañeda, J. Moreno-Cadenas, L. M. Flores-Nava\",\"doi\":\"10.1109/ICEEE.2013.6676052\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This work describes the development and FPGA implementation of a solar panel emulator. First we created the electric analog model of the solar panel using the Mentor Graphics framework, using the irradiance and temperature variables of a meteorological database as input signals and then obtaining the short circuit current and the open circuit voltage parameters to finally train an artificial neural network using Matlab, to perform the modeling of the response of the solar panel. Once the neural network was optimized, this was described in VHDL to simulate its response, to finally make its implementation in FPGA digital device and to be able to compare these results with those of a commercial solar panel.\",\"PeriodicalId\":226547,\"journal\":{\"name\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"volume\":\"35 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2013-12-02\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"14\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICEEE.2013.6676052\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2013 10th International Conference on Electrical Engineering, Computing Science and Automatic Control (CCE)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICEEE.2013.6676052","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FGPA development and implementation of a solar panel emulator
This work describes the development and FPGA implementation of a solar panel emulator. First we created the electric analog model of the solar panel using the Mentor Graphics framework, using the irradiance and temperature variables of a meteorological database as input signals and then obtaining the short circuit current and the open circuit voltage parameters to finally train an artificial neural network using Matlab, to perform the modeling of the response of the solar panel. Once the neural network was optimized, this was described in VHDL to simulate its response, to finally make its implementation in FPGA digital device and to be able to compare these results with those of a commercial solar panel.