Published April 2014 | Version v1
Journal article

Improving the performance of PV systems by faults detection using GISTEL approach

  • 1. Laboratoire des Semi-conducteurs et Matériaux Fonctionnels, Université Amar Telidji de Laghouat, BP 37G, Laghouat 03000 (Algeria)
  • 2. Department of Physics, Faculty of Science, Abou Bekr Belkaid University, Tlemcen, BP 119, Tlemcen 13000 (Algeria)
  • 3. MNT Group, Electronic Engineering Department, UPC-BarcelonaTech, Campus Nord UPC, Jordi Girona 1-3, 08034 Barcelona (Spain)

Description

Highlights: • A new approach for detecting the faults in PV systems was explored. • A simulation results of an estimation of a global solar radiation was reached. • An algorithm for detecting the faults is proposed. - Abstract: In this paper, we present a new approach for detecting the faults in the photovoltaic systems based on the satellite image approach for estimating solar radiation data and DC output power calculations for detecting the failures. At first stage, the estimation of the hourly global horizontal solar radiation data has been evaluated by using the GISTEL (Gisement solaire par télédetection: Solar Radiation by Teledectection) model improved by the fuzzy logic technique. Thus, the results were compared with the ground solar radiation measurements. On the other hand, the comparison between the simulated and measured output DC powers was reached to find the nature of the faults in the PV array. The results showed a good accuracy and the simple implementation of the proposed approach. The estimation of the hourly solar radiation presents an NRMSE <0.22 using GISTEL model improved by fuzzy logic comparing with the estimation without fuzzy logic with an NRMSE = 0.2885 for clear sky and NRMSE = 0.2852 comparing with NRMSE = 0.3121 for cloudy sky

Availability note (English)

Available from http://dx.doi.org/10.1016/j.enconman.2014.01.030

Additional details

Identifiers

DOI
10.1016/j.enconman.2014.01.030;
PII
S0196-8904(14)00074-0;

Publishing Information

Journal Title
Energy Conversion and Management
Journal Volume
80
Journal Page Range
p. 298-304
ISSN
0196-8904
CODEN
ECMADL

INIS

Country of Publication
United Kingdom
Country of Input or Organization
International Atomic Energy Agency (IAEA)
INIS RN
46022534
Subject category
S29: ENERGY PLANNING, POLICY AND ECONOMY;
Descriptors DEI
ALGORITHMS; COMPARATIVE EVALUATIONS; DETECTION; FUZZY LOGIC; IMAGES; PERFORMANCE; PHOTOVOLTAIC EFFECT; SATELLITES; SIMULATION; SOLAR RADIATION
Descriptors DEC
EVALUATION; MATHEMATICAL LOGIC; PHOTOELECTRIC EFFECT; RADIATIONS; STELLAR RADIATION

Optional Information

Copyright
Copyright (c) 2014 Elsevier Science B.V., Amsterdam, The Netherlands, All rights reserved.