Correlation of photovoltaics plant performance metrics
- Authors: Vumbugwa, Monphias
- Date: 2018
- Subjects: Photovoltaic cells , Perfomance -- Evaluation , Thin films
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/45657 , vital:38924
- Description: The generation of electrical energy using Photovoltaic (PV) technology has increased globally with the decrease in the cost of PV systems and the rise in electrical power demand. In South Africa, the support by the government in implementing the Renewable Energy Independent Power Producer Procurement Programme (REIPPPP) has seen a growth in PV system deployment and investment in roof and ground mounted, stand alone and grid connected PV plants. This rapid growth shows that the PV industry is becoming highly competitive as there is a shift to low carbon emissions and it is anticipated to be the most affordable source of electricity. Hence, there is need to develop maintenance and fault diagnosis expertise and capabilities in the PV industry, which can in turn improve the dependability, productiveness and lifespan of PV systems. Solar PV modules directly receive and convert solar irradiance into electricity and may not generate the expected optimum energy due to abnormalities which arise when they are exposed to harsh unfavorable environmental conditions in the field. Thermal Infrared (TIR) imaging is widely used as a fault diagnosis tool in operating PV modules and mostly in large PV power plants. Therefore, there is need to research the interpretation of the observed thermal signatures and the impact that the anomalies have on electrical output of the system so as to improve the PV maintenance systems. This research focuses on identifying performance limiting defects using an Infra-Red (I-R) camera, mounted on an Unmanned Aerial Vehicle (UAV), to understand the effect of thermal signatures on current-voltage (I-V) characteristics of PV module strings. Aerial TIR imaging using a UAV can rapidly identify abnormalities in operational PV modules strings as hotspots. Any deviation of the string I-V curve, from the expected, indicates a problem with one or more PV modules in the string. However, locating the faulty module involves measuring I-V parameters of the individual modules in a string, which is not feasible in large PV power plants. Therefore, there is a need to estimate the power loss associated with the thermal signatures in PV module strings. Visual inspection may help in identifying the exact cause of some hotspots, while other hotspots need special characterization techniques, such as Electroluminescence (EL) and UV Fluorescence (UV-F), which can indicate if a solar cell is cracked or has weak busbars or contact finger connections.
- Full Text:
- Date Issued: 2018
- Authors: Vumbugwa, Monphias
- Date: 2018
- Subjects: Photovoltaic cells , Perfomance -- Evaluation , Thin films
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/45657 , vital:38924
- Description: The generation of electrical energy using Photovoltaic (PV) technology has increased globally with the decrease in the cost of PV systems and the rise in electrical power demand. In South Africa, the support by the government in implementing the Renewable Energy Independent Power Producer Procurement Programme (REIPPPP) has seen a growth in PV system deployment and investment in roof and ground mounted, stand alone and grid connected PV plants. This rapid growth shows that the PV industry is becoming highly competitive as there is a shift to low carbon emissions and it is anticipated to be the most affordable source of electricity. Hence, there is need to develop maintenance and fault diagnosis expertise and capabilities in the PV industry, which can in turn improve the dependability, productiveness and lifespan of PV systems. Solar PV modules directly receive and convert solar irradiance into electricity and may not generate the expected optimum energy due to abnormalities which arise when they are exposed to harsh unfavorable environmental conditions in the field. Thermal Infrared (TIR) imaging is widely used as a fault diagnosis tool in operating PV modules and mostly in large PV power plants. Therefore, there is need to research the interpretation of the observed thermal signatures and the impact that the anomalies have on electrical output of the system so as to improve the PV maintenance systems. This research focuses on identifying performance limiting defects using an Infra-Red (I-R) camera, mounted on an Unmanned Aerial Vehicle (UAV), to understand the effect of thermal signatures on current-voltage (I-V) characteristics of PV module strings. Aerial TIR imaging using a UAV can rapidly identify abnormalities in operational PV modules strings as hotspots. Any deviation of the string I-V curve, from the expected, indicates a problem with one or more PV modules in the string. However, locating the faulty module involves measuring I-V parameters of the individual modules in a string, which is not feasible in large PV power plants. Therefore, there is a need to estimate the power loss associated with the thermal signatures in PV module strings. Visual inspection may help in identifying the exact cause of some hotspots, while other hotspots need special characterization techniques, such as Electroluminescence (EL) and UV Fluorescence (UV-F), which can indicate if a solar cell is cracked or has weak busbars or contact finger connections.
- Full Text:
- Date Issued: 2018
On the characterization of solar cells using advanced imaging techniques
- Authors: Dix-Peek, Ross Michael
- Date: 2018
- Subjects: Photovoltaic cells
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/17944 , vital:28544
- Description: Photovoltaic (PV) cells are devices capable of producing electricity - in particular, from the abundant resource of sunlight. Solar energy (from PV cells) provides a sustainable alternative to fossil fuel energy sources such as coal and oil. PV cells are typically strung in series in PV modules to generate the current and voltage required for commercial use. However, PV cell performance can be limited by defects and degradation. Under operational conditions due to mismatch and shading, individual cells within a PV module can be forced to operate in their reverse bias regime. Depending on the severity of the reverse bias and the defects present in the cell, the longevity of the cell and/or the module can be affected. Reverse bias (assuming bypass diodes are absent) can result in localised heating that can affect the encapsulant polymer’s longevity as well as degrade the cell’s performance over time. However, under more severe reverse bias, the cell could fail, drastically affecting the performance of the module. PV cells can be characterised using various opto-electronic non-destructive techniques, this provides a set of powerful tools which allow the application of multiple such techniques to the same sample. Furthermore, this allows for an in-depth study of the device. Dark Current-Voltage (I-V) measurements, Electroluminescence (EL), Infrared (IR) thermography, Light Beam Induced Current (LBIC) measurements, and the associated techniques are all examples of such tools and are used within this study. An experimental setup was developed to perform dark I-V measurements, EL imaging, IR thermography and LBIC measurements. Part of the development of the experimental setup was the design of an enclosure in which to perform all the measurements. The enclosure minimised internal reflection, and isolated the experiment from electromagnetic radiation. Due to the complex mathematical model applied to the I-V curve, an Evolutionary Algorithm was used to determine optimal parameter values for the equation. More specifically, a Genetic Algorithm was used in the Parameter Optimisation (or Extraction) of the dark I-V parameters based upon the two-diode model for PV cells. The resulting parameters give an indication of the material and device quality. However, to determine the spatial distribution of the defects that effect the I-V response of the device, various imaging techniques were utilised. LBIC is a technique that uses a focussed light beam to raster scan across the surface of a PV cell. The local photo-induced current/voltage can then be measured and compiled into a response map. LBIC was used to determine the local current response across the device. The intensity distribution of EL signal is related to the local junction voltage and the local quantum efficiency. EL intensity imaging with a Si CCD camera was used to determine the spatial distribution of features visible both in the forward bias and in the reverse bias. The experimental setup utilised had a micron scale resolution. A voltage dependent approach was utilised to further characterise features observed. In forward bias, the local junction varies across the device due to parasitic resistances such as series and shunt resistance. At higher forward bias conditions (in the vicinity of and higher than maximum power voltage), series resistance becomes a limiting factor. Therefore, utilising a voltage dependent approach allows for the determination of a series resistance map from voltage dependent EL images. In reverse bias, localised radiative processes can be imaged. These radiative processes are related to defects in the device, such as Al stains, FeSi2 needles and avalanche breakdown. The processes are related to highly localised current flow; this causes localised heating which degrades the device. The voltage dependent Reverse Bias EL (ReBEL) imaging was also used to determine the local breakdown voltage of radiative reverse features. Dark IR thermography is a technique used in the identification of high current sites that leads to localised Joule heating, particularly in reverse bias. In this study, thermography was used to identify breakdown sites and shunts. The results of this study allow for an in-depth analysis of defects found in multi-crystalline Si PV cells using the opto-electronic techniques mentioned above. The multi-pronged approach allowed from a comparison of the various opto-electronic techniques, as well as a more in-depth characterisation of the defects than if only one technique was used.
- Full Text:
- Date Issued: 2018
- Authors: Dix-Peek, Ross Michael
- Date: 2018
- Subjects: Photovoltaic cells
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: http://hdl.handle.net/10948/17944 , vital:28544
- Description: Photovoltaic (PV) cells are devices capable of producing electricity - in particular, from the abundant resource of sunlight. Solar energy (from PV cells) provides a sustainable alternative to fossil fuel energy sources such as coal and oil. PV cells are typically strung in series in PV modules to generate the current and voltage required for commercial use. However, PV cell performance can be limited by defects and degradation. Under operational conditions due to mismatch and shading, individual cells within a PV module can be forced to operate in their reverse bias regime. Depending on the severity of the reverse bias and the defects present in the cell, the longevity of the cell and/or the module can be affected. Reverse bias (assuming bypass diodes are absent) can result in localised heating that can affect the encapsulant polymer’s longevity as well as degrade the cell’s performance over time. However, under more severe reverse bias, the cell could fail, drastically affecting the performance of the module. PV cells can be characterised using various opto-electronic non-destructive techniques, this provides a set of powerful tools which allow the application of multiple such techniques to the same sample. Furthermore, this allows for an in-depth study of the device. Dark Current-Voltage (I-V) measurements, Electroluminescence (EL), Infrared (IR) thermography, Light Beam Induced Current (LBIC) measurements, and the associated techniques are all examples of such tools and are used within this study. An experimental setup was developed to perform dark I-V measurements, EL imaging, IR thermography and LBIC measurements. Part of the development of the experimental setup was the design of an enclosure in which to perform all the measurements. The enclosure minimised internal reflection, and isolated the experiment from electromagnetic radiation. Due to the complex mathematical model applied to the I-V curve, an Evolutionary Algorithm was used to determine optimal parameter values for the equation. More specifically, a Genetic Algorithm was used in the Parameter Optimisation (or Extraction) of the dark I-V parameters based upon the two-diode model for PV cells. The resulting parameters give an indication of the material and device quality. However, to determine the spatial distribution of the defects that effect the I-V response of the device, various imaging techniques were utilised. LBIC is a technique that uses a focussed light beam to raster scan across the surface of a PV cell. The local photo-induced current/voltage can then be measured and compiled into a response map. LBIC was used to determine the local current response across the device. The intensity distribution of EL signal is related to the local junction voltage and the local quantum efficiency. EL intensity imaging with a Si CCD camera was used to determine the spatial distribution of features visible both in the forward bias and in the reverse bias. The experimental setup utilised had a micron scale resolution. A voltage dependent approach was utilised to further characterise features observed. In forward bias, the local junction varies across the device due to parasitic resistances such as series and shunt resistance. At higher forward bias conditions (in the vicinity of and higher than maximum power voltage), series resistance becomes a limiting factor. Therefore, utilising a voltage dependent approach allows for the determination of a series resistance map from voltage dependent EL images. In reverse bias, localised radiative processes can be imaged. These radiative processes are related to defects in the device, such as Al stains, FeSi2 needles and avalanche breakdown. The processes are related to highly localised current flow; this causes localised heating which degrades the device. The voltage dependent Reverse Bias EL (ReBEL) imaging was also used to determine the local breakdown voltage of radiative reverse features. Dark IR thermography is a technique used in the identification of high current sites that leads to localised Joule heating, particularly in reverse bias. In this study, thermography was used to identify breakdown sites and shunts. The results of this study allow for an in-depth analysis of defects found in multi-crystalline Si PV cells using the opto-electronic techniques mentioned above. The multi-pronged approach allowed from a comparison of the various opto-electronic techniques, as well as a more in-depth characterisation of the defects than if only one technique was used.
- Full Text:
- Date Issued: 2018
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