Fault Detection for Photovoltaic Systems Using Multivariate Analysis With Electrical and Environmental Variables

Fault detection and repair of the components of photovoltaic (PV) systems are essential to avoid economic losses and facility accidents, thereby ensuring reliable and safe systems. This article presents a method to detect faults in a PV system based on power ratio (PR), voltage ratio (VR), and current ratio (IR). The lower control limit (LCL) and upper control limit (UCL) of each ratio were defined using the data of a test site system under normal operating conditions. If PR exceeded the set range, the algorithm considered a fault. Subsequently, PR and IR were examined via the algorithm to diagnose faults in the system as series, parallel, or total faults. The results showed that PR exceeded the designated range between LCL (0.93) and UCL (1.02) by dropping to 0.91–0.68, 0.88–0.62, and 0.66–0.33 for series, total, and parallel faults, respectively. Moreover, VR exceeded the LCL (0.99) and UCL (1.01) by 0.95–0.69 and 0.91–0.62 for series and total faults, respectively, but not under parallel faults condition. IR did not change in series and total faults but exceeded the range of LCL (0.93) and UCL (1.05) by dropping to 0.66–0.33. Thus, faults in PV systems can be detected and diagnosed by analyzing quantitative output values.

[1]  Björn Müller,et al.  Performance Ratio Revisited: Are PR >90% Realistic? , 2011 .

[2]  Farid Touati,et al.  Effects of Environmental and Climatic Conditions on PV Efficiency in Qatar , 2013 .

[3]  Saad Mekhilef,et al.  Effect of dust, humidity and air velocity on efficiency of photovoltaic cells , 2012 .

[4]  Ying Sun,et al.  Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches , 2018 .

[5]  Soteris A. Kalogirou,et al.  Fault detection and diagnosis methods for photovoltaic systems: A review , 2018, Renewable and Sustainable Energy Reviews.

[6]  Bharath Seshadri,et al.  Temperature Dependent Photovoltaic (PV) Efficiency and Its Effect on PV Production in the World – A Review☆ , 2013 .

[7]  C. Spearman.  The proof and measurement of association between two things. , 2015, International journal of epidemiology.

[8]  E. El-Saadany,et al.  Enhanced Reconfiguration Method for Reducing Mismatch Losses in PV Systems , 2017, IEEE Journal of Photovoltaics.

[9]  William E. Boyson,et al.  Photovoltaic array performance model. , 2004 .

[10]  Tamer Khatib,et al.  Optimization of photovoltaic modules tilt angle for Oman , 2013, 2013 IEEE 7th International Power Engineering and Optimization Conference (PEOCO).

[11]  H. Ahn,et al.  Prediction Model for PV Performance With Correlation Analysis of Environmental Variables , 2019, IEEE Journal of Photovoltaics.

[12]  Andy Walker.  PV O&M Cost Model and Cost Reduction , 2017 .

[13]  Byeong Gwan Bhang,et al.  Power Performance of Bifacial c-Si PV Modules With Different Shading Ratios , 2019, IEEE Journal of Photovoltaics.

[14]  H. Haeberlin.  Normalized Representation of Energy and Power for Analysis of Performance and On-line Error Detection in PV-Systems , 2003 .

[15]  Jin Choi,et al.  Power Prediction of Bifacial Si PV Module with Different Reflection Conditions on Rooftop , 2018, Applied Sciences.

[16]  Peijie Lin,et al.  Deep residual network based fault detection and diagnosis of photovoltaic arrays using current-voltage curves and ambient conditions , 2019, Energy Conversion and Management.

[17]  L. Cristaldi,et al.  Characterization of photovoltaic panels: The effects of dust , 2012, 2012 IEEE International Energy Conference and Exhibition (ENERGYCON).

[18]  O. Westbrook,et al.  Ambient temperature correction of photovoltaic system performance data , 2014, 2014 IEEE 40th Photovoltaic Specialist Conference (PVSC).

[19]  Young-Seok Jung,et al.  Design Factor Calculation and Analysis of Grid-Connected Photovoltaic System , 2013 .

[20]  Hyung-Keun Ahn,et al.  Prediction Model of Photovoltaic Module Temperature for Power Performance of Floating PVs , 2018 .

[21]  Tingting Pei,et al.  A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation , 2019, Energies.

[22]  John K. Kaldellis,et al.  Temperature and wind speed impact on the efficiency of PV installations. Experience obtained from outdoor measurements in Greece , 2014 .

[23]  Neungsoo Park,et al.  Multi-Layer RNN-based Short-term Photovoltaic Power Forecasting using IoT Dataset , 2019, 2019 AEIT International Annual Conference (AEIT).

[24]  Chandrasegar Thirumalai,et al.  Analysing the concrete compressive strength using Pearson and Spearman , 2017, 2017 International conference of Electronics, Communication and Aerospace Technology (ICECA).

[25]  Abdelhamid Rabhi,et al.  Neuro-Fuzzy fault detection method for photovoltaic systems , 2014 .

[26]  T. Townsend,et al.  Effects of irradiance and other factors on PV temperature coefficients , 1991, The Conference Record of the Twenty-Second IEEE Photovoltaic Specialists Conference - 1991.