光伏板仿真器在FPGA技术中采用了ANFIS方法

F. Gómez-Castañeda, Gerardo Marcos Tornez-Xavier, L. M. Flores-Nava, O. Arellano-Cárdenas, J. Moreno-Cadenas
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引用次数: 9

摘要

在本文中,我们介绍了基于自适应网络的模糊推理系统(ANFIS)的FPGA实现,该系统具有双输入架构,每个输入具有三个隶属函数和九个模糊规则,用于建立光伏板模拟器。首先用Mentor Graphics Suite的ELDO工具模拟光伏板的电模拟模型,输入来自气象数据库的辐照度和温度,这样我们就可以得到面板的短路电流(Isc)和开路电压(Voc)。利用这些信息,在Matlab环境下训练ANFIS来近似光伏板的响应。训练分别针对电流和电压进行,一旦达到最小误差参数,它们就被下载到FPGA实现的架构中,以评估其性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Photovoltaic panel emulator in FPGA technology using ANFIS approach
In this manuscript we present the implementation in FPGA of ANFIS system (Adaptive Network-based Fuzzy Inference Systems) for a two-input architecture with three membership functions per input and nine fuzzy rules, used to set up a photovoltaic panel emulator. The starting point is the photovoltaic panel electric analog model simulated with ELDO, a tool of Mentor Graphics Suite, having as inputs irradiation and temperature from a meteorological data base so we can obtain the short-circuit current (Isc) and open circuit voltage (Voc) of the panel. With this information, ANFIS was trained within Matlab environment to approximate the photovoltaic panel response. The training was carried out for both, current and voltage, independently, and once achieved minimum error parameters, they were downloaded into the FPGA implemented architecture in order to assess its performance.
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