Eventos Anais de eventos
COBEM 2021
26th International Congress of Mechanical Engineering
COMPARISON OF TEMPERATURE FORECASTING MODELS OF PHOTOVOLTAIC MODULES OPERATING UNDER TROPICAL CLIMATE
Submission Author:
Leticia de Oliveira Santos , CE
Co-Authors:
Ana Patricia Fontenele Barros, Leticia de Oliveira Santos, Renata Imaculada Soares Pereira, PAULO CARVALHO
Presenter: Leticia de Oliveira Santos
doi://10.26678/ABCM.COBEM2021.COB2021-2039
Abstract
Several climatic factors affect the performance of photovoltaic (PV) modules, mainly solar irradiation, ambient temperature, and wind speed. The first two has the greatest impact on PV cell performance, which is directly related to the cells operating temperature. The solar irradiation is converted by PV modules partly into electricity and partly into heat, causing an inversely proportional ratio: the higher the cells operating temperature, the lower their efficiency. Our research compares measured PV modules operating temperature data with theoretical values estimated through models from the literature, aiming to find an equation that best suits the tropical climate of the PV plant site under study. The experimental data in the period of January to November 2020 was obtained from the Laboratory of Alternative Energies (LEA) of the Federal University of Ceará (UFC). The Skoplaki and Palyvos model, which considers ambient temperature, solar irradiation and wind speed, shows the best adjustment with the thermal behavior of the PV modules under the analyzed climatic conditions. This model showed the lowest average percentage error of 4.41%, with a maximum error of 5.51°C, when compared to the experimental data. The CLEFS CEA and Duffie & Beckman models occupy, respectively, the second and third place of the methods that best suit the data, with similar results, showing an average percentage error of 6.17% and 6.24%, respectively. The largest errors between measured and estimated values occur in the early morning and late afternoon; the smallest errors are between 10:00 a.m. and 02:00 p.m.
Keywords
Data analysis, Forecasting models, Photovoltaic module temperature, Renewable energy.
