Fault diagnosis of building integrated PV generator: A metaheuristic technique

Hachana, Oussama; Hemsas, Kamel Eddine; Tina, Giuseppe Marco

doi:10.1109/irec.2015.7110911

Cited by 5 publications

(2 citation statements)

References 11 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Moreover, the number of thermal cameras increases with the implementation area, raising the cost of large-scale PV power plant construction. Studies conducted on fault diagnosis have included additional sensors [4,5]…”

Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Fault Detector for Photovoltaic Module Array

2019

View full text Add to dashboard Cite

This study proposes a binary search-based fault detection system for photovoltaic (PV) modules to ameliorate the deficiencies in the existing fault detectors for PV module arrays. The proposed system applies a single-chip microcontroller to execute the binary search algorithm. Moreover, to overcome multi-node voltage detection and reduce the number of integrated circuit components, an analog switch is used to perform detection channel switching; the detection results are displayed on a software platform developed using Visual C#. The proposed system does not require learning to execute the fault diagnosis of PV module arrays and has advantages including high accuracy and low construction costs. Finally, to verify the feasibility of the proposed system, this study simulated the abnormal situations of actual modules and applied the binary search algorithm for maximum power point tracking to detect malfunctions of the PV module arrays.

show abstract

Section: Introductionmentioning

confidence: 99%

Development of a Low-Cost Fault Detector for Photovoltaic Module Array

2019

View full text Add to dashboard Cite

show abstract

“…Bonsignore et al (2014) developed a neuro-fuzzy fault detection method that identifies faulty behavior by comparing the value of six parameters along with the I-V curves in normal and faulty conditions. Hachana et al (2015) developed a PV emulator for both normal and abnormal operating conditions. The amount of power losses along with the information extracted from this emulator was used to detect defects.…”

Section: Introductionmentioning

confidence: 99%

Automatic fault detection for Building Integrated Photovoltaic (BIPV) systems using time series methods

Shahandashti

Ashuri

Mostaan

2018

BEPAM

View full text Add to dashboard Cite

Purpose Faults in the actual outdoor performance of Building Integrated Photovoltaic (BIPV) systems can go unnoticed for several months since the energy productions are subject to significant variations that could mask faulty behaviors. Even large BIPV energy deficits could be hard to detect. The purpose of this paper is to develop a cost-effective approach to automatically detect faults in the energy productions of BIPV systems using historical BIPV energy productions as the only source of information that is typically collected in all BIPV systems. Design/methodology/approach Energy productions of BIPV systems are time series in nature. Therefore, time series methods are used to automatically detect two categories of faults (outliers and structure changes) in the monthly energy productions of BIPV systems. The research methodology consists of the automatic detection of outliers in energy productions, and automatic detection of structure changes in energy productions. Findings The proposed approach is applied to detect faults in the monthly energy productions of 89 BIPV systems. The results confirm that outliers and structure changes can be automatically detected in the monthly energy productions of BIPV systems using time series methods in presence of short-term variations, monthly seasonality, and long-term degradation in performance. Originality/value Unlike existing methods, the proposed approach does not require performance ratio calculation, operating condition data, such as solar irradiation, or the output of neighboring BIPV systems. It only uses the historical information about the BIPV energy productions to distinguish between faults and other time series properties including seasonality, short-term variations, and degradation trends.

show abstract

Introduction to Renewable Energy Market and Metaheuristic Algorithms for Condition Monitoring of Photovoltaic Parameter Estimation

Kumar

2020

Metaheuristic and Evolutionary Computation: Algorithms and Applications

View full text Add to dashboard Cite

Fault diagnosis of building integrated PV generator: A metaheuristic technique

Cited by 5 publications

References 11 publications

Development of a Low-Cost Fault Detector for Photovoltaic Module Array

Development of a Low-Cost Fault Detector for Photovoltaic Module Array

Automatic fault detection for Building Integrated Photovoltaic (BIPV) systems using time series methods

Introduction to Renewable Energy Market and Metaheuristic Algorithms for Condition Monitoring of Photovoltaic Parameter Estimation

Contact Info

Product

Resources

About