Mismatch Based Diagnosis of PV Fields Relying on Monitored String Currents

This paper presents a DC side oriented diagnostic method for photovoltaic fields which operates on string currents previously supplied by an appropriate monitoring system. The relevance of the work relies on the definition of an effective and reliable day-by-day target for the power that every string of the field should have produced. The procedure is carried out by comparing the instantaneous power produced by all solar strings having the same orientation and by attributing, as producible power for all of them, the maximum value. As figure of merit, the difference between the maximum allowed energy production (evaluated as the integral of the power during a defined time interval) and the energy actually produced by the strings is defined. Such a definition accounts for both weather and irradiance conditions, without needing additional sensors. The reliability of the approach was experimentally verified by analyzing the performance of two medium size solar fields that were monitored over a period of four years. Results allowed quantifying energy losses attributable to underperforming solar strings and precisely locating their position in the field.

[1]  C. Nagamani,et al.  A Method to Detect Photovoltaic Array Faults and Partial Shading in PV Systems , 2016, IEEE Journal of Photovoltaics.

[2]  Bruno Ando,et al.  Sentinella: Smart Monitoring of Photovoltaic Systems at Panel Level , 2015, IEEE Transactions on Instrumentation and Measurement.

[3]  Vincenzo d'Alessandro,et al.  Monitoring and Diagnostics of PV Plants by a Wireless Self-Powered Sensor for Individual Panels , 2016, IEEE Journal of Photovoltaics.

[4]  V. d’Alessandro,et al.  Effective real-time performance monitoring and diagnostics of individual panels in PV plants , 2013, 2013 International Conference on Clean Electrical Power (ICCEP).

[5]  A. Massi Pavan,et al.  Fault diagnosis in photovoltaic arrays , 2015, 2015 International Conference on Clean Electrical Power (ICCEP).

[6]  Charles R. Sullivan,et al.  Partial-Shading Assessment of Photovoltaic Installations via Module-Level Monitoring , 2014, IEEE Journal of Photovoltaics.

[7]  J. Ji,et al.  Safety Analysis of Solar Module under Partial Shading , 2015 .

[8]  Loredana Cristaldi,et al.  Reference strings for statistical monitoring of the energy performance of photovoltaic fields , 2015, 2015 International Conference on Clean Electrical Power (ICCEP).

[9]  Takashi Oozeki,et al.  Monitoring and Evaluation of Photovoltaic System , 2013 .

[10]  Ye Zhao,et al.  Fault experiments in a commercial-scale PV laboratory and fault detection using local outlier factor , 2014, 2014 IEEE 40th Photovoltaic Specialist Conference (PVSC).

[11]  A. Massi Pavan,et al.  Monitoring, diagnosis, and power forecasting for photovoltaic fields: A review , 2017 .

[12]  S. Ben-Menahem,et al.  Online photovoltaic array hot-spot Bayesian diagnostics from streaming string-level electric data , 2012, 2012 38th IEEE Photovoltaic Specialists Conference.

[13]  I. Nakir,et al.  An Improved Matlab-Simulink Model of PV Module considering Ambient Conditions , 2014 .

[14]  A. Rabhi,et al.  Partial shading fault diagnosis in PV system with discrete wavelet transform (DWT) , 2014, 2014 International Conference on Renewable Energy Research and Application (ICRERA).

[15]  Masashi Baba,et al.  Examination of fault detection technique in PV systems , 2013 .

[16]  P. Guerriero,et al.  A PV AC-module based on coupled-inductors boost DC/AC converter , 2014, 2014 International Symposium on Power Electronics, Electrical Drives, Automation and Motion.

[17]  Lorenzo Ciani,et al.  Design and implementation of a on-board device for photovoltaic panels monitoring , 2013, 2013 IEEE International Instrumentation and Measurement Technology Conference (I2MTC).

[18]  Federico Bizzarri,et al.  Monitoring performance and efficiency of photovoltaic parks , 2015 .

[19]  Radu Platon,et al.  Online Fault Detection in PV Systems , 2015, IEEE Transactions on Sustainable Energy.