Performance Analysis and Fault Diagnosis Method for Concentrator Photovoltaic Modules

Abstract

Abstract-Concentrator Photovoltaic (CPV) systems use high efficiency multi-junction solar cells with efficiencies >40%, but the module efficiency is often much lower. The increased complexity of a CPV module, with optics, receiver and the tracker give an increased probability that faults will arise during the operational lifetime. In addition, a location like India has varied atmospheric conditions that further complicate the diagnosis of faults. It is therefore important to decouple effects due to the external environment (such as the atmosphere) from effects due to the degradation of the module. By applying a computer model to outdoor CPV test data in Bangalore, India we have established a method to assess the performance of the CPV module and finally we present a method to diagnose faults in the module.

The potential for concentrator photovoltaics: A feasibility study in India

“…We employ a bottom‐up simulation approach to simulate a CPV system, where we use computer models for the solar cell, optical system, and spectral irradiance. We perform these calculations using a Python 3 framework known as SolCore (described in more detail in ) that encapsulates all relevant models for concentrator PV modules, multi‐junction solar cells, and spectral irradiance while also connecting to a database for convenient access to meteorological data . To simulate a CPV module, the component solar cell semiconductor material properties and dimensions are supplied together with the optical transfer function, incident solar spectrum, and cell temperature.…”

“…This methodology has been validated against outdoor test data from Toyohashi, Japan and recently Bangalore, India . In the Bangalore study, the module developed a fault that resulted in high mismatch of cell currents within the module and high series resistance losses.…”

Super-Multi-Junction Solar Cells—Device Configuration with the Potential for More Than 50% Annual Energy Conversion Efficiency (Non-Concentration)

“…Another crucial point is that the distribution of atmospheric parameters, especially aerosol density, was worst for the general performance on multi-junction solar cells with more than three junctions, even though the airmass level (20 • of latitude) is low. The worst-case distribution of the aerosol density is close to North India [57][58][59][60], and this region is known as one of the worst areas for energy generation in multi-junction solar cells in the field experience [104,105]. This is another reason that we need to develop an annual performance model based on realistic atmospheric conditions with a probability the realistic variations.…”

Super-Multi-Junction Solar Cell, Device Configuration with the Potential of More Than 50 % of the Annual Energy Conversion Efficiency (Non-Concentration)

“…Another crucial point is that the distribution of the atmospheric parameters, especially aerosol density was the worst for the general performance to multi-junction solar cells with more than three junctions, even though the airmass level (20° of latitude) is low. The worst-case distribution of the aerosol density was closed to North India [57][58][59][60], and this region was known as one of the worst areas for the energy generation to the multi-junction solar cells in the field experience [109][110]. This is another reason why we need to develop an annual performance model based on the realistic atmospheric conditions with a probability of the realistic variations.…”