An ANFIS-Based Modeling Comparison Study for Photovoltaic Power at Different Geographical Places in Mexico

Nun Pitalúa-Díaz,Enrique Fernando Velázquez-Contreras,Yasuhiro Matsumoto,Fernando Arellano-Valmaña,Ricardo Arturo Pérez-Enciso,Hussain Alazki,Enrique J Herrera-López,A García-Juárez,Jose A Ruz-Hernandez,Jesús Fernando Hinojosa-Palafox

doi:10.3390/en12142662

Abstract

In this manuscript, distinct approaches were used in order to obtain the best electrical power estimation from photovoltaic systems located at different selected places in Mexico. Multiple Linear Regression (MLR) and Gradient Descent Optimization (GDO) were applied as statistical methods and they were compared against an Adaptive Neuro-Fuzzy Inference System (ANFIS) as an intelligent technique. The data gathered involved solar radiation, outside temperature, wind speed, daylight hour and photovoltaic power; collected from on-site real-time measurements at Mexico City and Hermosillo City, Sonora State. According to our results, all three methods achieved satisfactory performances, since low values were obtained for the convergence error. The GDO improved the MLR results, minimizing the overall error percentage value from 7.2% to 6.9% for Sonora and from 2.0% to 1.9% for Mexico City; nonetheless, ANFIS overcomes both statistical methods, achieving a 5.8% error percentage value for Sonora and 1.6% for Mexico City. The results demonstrated an improvement by applying intelligent systems against statistical techniques achieving a lesser mean average error.

Highlights

Considerable research has been developed internationally in the field of photovoltaic systems and power generation [1,2,3]
Seven different cases or sets of data were computed to analyze which estimation technique executes a better performance for the Hermosillo site (HS) and the Mexico City site (MCS)
Every case was represented by data collected during a whole month; the first case corresponds to six months of collected data, while the seventh case stands for the accumulation of all data

Summary

Introduction

Considerable research has been developed internationally in the field of photovoltaic systems and power generation [1,2,3]. Mexico is a country that receives abundant solar energy, with the northwest region being the one with the highest annual incidence of solar radiation, achieving radiation indexes between 5.6 and 6.2 kWh/m2 per day; its advances on the photovoltaic field are scarse nowadays, there are many possibilities of research in this topic [4]. There are many scientific reports on statistical methods to estimate power generation [5,6,7,8]. A satisfactory photovoltaic power estimation involving meteorological variables was carried out in [10] in which a Gradient Descent Optimization (GDO) minimizes the error value between the real and estimated variables after many iterations; even so, it is mentioned that other techniques may obtain better results despite their lower or greater complexity.

Objectives

Results

Conclusion