Projects per year
Abstract
Improving PV system reliability and reducing maintenance and operating costs have become important factors in increasing the competitiveness of PV. Addressing these issues requires diagnostic methods that can detect and identify the occurrence and cause of power loss in the PV system, be it external, such as shading or soiling, or degradation or failure of the PV modules and balance-of-system components. This allows for performing preventive and/or reparative maintenance, thus minimizing further losses and costs.
This article proposes a complete diagnostic method for detecting shading, increased series-resistance losses, and potential-induced degradation of the PV generator by analysing changes its current-voltage characteristic curve. The diagnostic method is based on parameters that can be easily calculated from the shape of the current-voltage curve, making it machine-analysis friendly and suitable for implementation in the power electronic converter. Moreover, the dimensionless formulation of the diagnostic parameters and the application of fuzzy logic in evaluating the diagnostic rules, make this method applicable to a wide range of standard crystalline silicon based PV systems.
The design and analysis of the diagnostic parameters and logic was performed based on module level tests on standard crystalline silicon PV modules, and were optimized to detect even small partial shading and increase series-resistance losses. To demonstrate the practical application and operation of this method, the diagnostic parameters and rules were applied “as is” to a field test setup consisting of a crystalline silicon based PV string and a commercial string inverter capable of measuring the I-V curve of the PV string, yielding a similar high-detection rate.
This article proposes a complete diagnostic method for detecting shading, increased series-resistance losses, and potential-induced degradation of the PV generator by analysing changes its current-voltage characteristic curve. The diagnostic method is based on parameters that can be easily calculated from the shape of the current-voltage curve, making it machine-analysis friendly and suitable for implementation in the power electronic converter. Moreover, the dimensionless formulation of the diagnostic parameters and the application of fuzzy logic in evaluating the diagnostic rules, make this method applicable to a wide range of standard crystalline silicon based PV systems.
The design and analysis of the diagnostic parameters and logic was performed based on module level tests on standard crystalline silicon PV modules, and were optimized to detect even small partial shading and increase series-resistance losses. To demonstrate the practical application and operation of this method, the diagnostic parameters and rules were applied “as is” to a field test setup consisting of a crystalline silicon based PV string and a commercial string inverter capable of measuring the I-V curve of the PV string, yielding a similar high-detection rate.
Original language | English |
---|---|
Journal | Solar Energy |
Volume | 119 |
Pages (from-to) | 29-44 |
ISSN | 0038-092X |
DOIs | |
Publication status | Published - Sept 2015 |
Keywords
- Diagnostic method
- Current-voltage characteristic
- Fault detection
- Increased series resistance,
- Partial shading
- Photovoltaic systems
- Potential-induced degradation
- Crystalline silicon
Fingerprint
Dive into the research topics of 'Diagnostic method for photovoltaic systems based on light I-V measurements'. Together they form a unique fingerprint.Projects
- 2 Finished
-
Remote Monitoring and Analysis of PV Systems
Séra, D., Spataru, S. V. & Rasmussen, B. D.
01/01/2013 → 01/01/2018
Project: Research
-
SPVSYS: Smart Photovoltaic Systems
Teodorescu, R., Séra, D., Kerekes, T., Borup, U., Spataru, S. V. & Bogdan, C.
01/01/2011 → 31/07/2015
Project: Research