Matching Items (5)

Filtering by

Clear all filters

151374-Thumbnail Image.png

26+ year old photovoltaic power plant: degradation and reliability evaluation of crystalline silicon modules - south array

Description

ABSTRACT As the use of photovoltaic (PV) modules in large power plants continues to increase globally, more studies on degradation, reliability, failure modes, and mechanisms of field aged modules are

ABSTRACT As the use of photovoltaic (PV) modules in large power plants continues to increase globally, more studies on degradation, reliability, failure modes, and mechanisms of field aged modules are needed to predict module life expectancy based on accelerated lifetime testing of PV modules. In this work, a 26+ year old PV power plant in Phoenix, Arizona has been evaluated for performance, reliability, and durability. The PV power plant, called Solar One, is owned and operated by John F. Long's homeowners association. It is a 200 kWdc, standard test conditions (STC) rated power plant comprised of 4000 PV modules or frameless laminates, in 100 panel groups (rated at 175 kWac). The power plant is made of two center-tapped bipolar arrays, the north array and the south array. Due to a limited time frame to execute this large project, this work was performed by two masters students (Jonathan Belmont and Kolapo Olakonu) and the test results are presented in two masters theses. This thesis presents the results obtained on the south array and the other thesis presents the results obtained on the north array. Each of these two arrays is made of four sub arrays, the east sub arrays (positive and negative polarities) and the west sub arrays (positive and negative polarities), making up eight sub arrays. The evaluation and analyses of the power plant included in this thesis consists of: visual inspection, electrical performance measurements, and infrared thermography. A possible presence of potential induced degradation (PID) due to potential difference between ground and strings was also investigated. Some installation practices were also studied and found to contribute to the power loss observed in this investigation. The power output measured in 2011 for all eight sub arrays at STC is approximately 76 kWdc and represents a power loss of 62% (from 200 kW to 76 kW) over 26+ years. The 2011 measured power output for the four south sub arrays at STC is 39 kWdc and represents a power loss of 61% (from 100 kW to 39 kW) over 26+ years. Encapsulation browning and non-cell interconnect ribbon breakages were determined to be the primary causes for the power loss.

Contributors

Agent

Created

Date Created
  • 2012

154078-Thumbnail Image.png

Characterization and analysis of long term field aged photovoltaic modules and encapsulant materials

Description

Photovoltaic (PV) module degradation is a well-known issue, however understanding the mechanistic pathways in which modules degrade is still a major task for the PV industry. In order to study

Photovoltaic (PV) module degradation is a well-known issue, however understanding the mechanistic pathways in which modules degrade is still a major task for the PV industry. In order to study the mechanisms responsible for PV module degradation, the effects of these degradation mechanisms must be quantitatively measured to determine the severity of each degradation mode. In this thesis multiple modules from three climate zones (Arizona, California and Colorado) were investigated for a single module glass/polymer construction (Siemens M55) to determine the degree to which they had degraded, and the main factors that contributed to that degradation. To explain the loss in power, various nondestructive and destructive techniques were used to indicate possible causes of loss in performance. This is a two-part thesis. Part 1 presents non-destructive test results and analysis and Part 2 presents destructive test results and analysis.

Contributors

Agent

Created

Date Created
  • 2015

153712-Thumbnail Image.png

Outdoor soiling loss characterization and statistical risk analysis of photovoltaic power plants

Description

This is a two-part thesis:

Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the

This is a two-part thesis:

Part 1 characterizes soiling losses using various techniques to understand the effect of soiling on photovoltaic modules. The higher the angle of incidence (AOI), the lower will be the photovoltaic (PV) module performance. Our research group has already reported the AOI investigation for cleaned modules of five different technologies with air/glass interface. However, the modules that are installed in the field would invariably develop a soil layer with varying thickness depending on the site condition, rainfall and tilt angle. The soiled module will have the air/soil/glass interface rather than air/glass interface. This study investigates the AOI variations on soiled modules of five different PV technologies. It is demonstrated that AOI effect is inversely proportional to the soil density. In other words, the power or current loss between clean and soiled modules would be much higher at a higher AOI than at a lower AOI leading to excessive energy production loss of soiled modules on cloudy days, early morning hours and late afternoon hours. Similarly, the spectral influence of soil on the performance of the module was investigated through reflectance and transmittance measurements. It was observed that the reflectance and transmittances losses vary linearly with soil density variation and the 600-700 nm band was identified as an ideal band for soil density measurements.

Part 2 of this thesis performs statistical risk analysis for a power plant through FMECA (Failure Mode, Effect, and Criticality Analysis) based on non-destructive field techniques and count data of the failure modes. Risk Priority Number is used for the grading guideline for criticality analysis. The analysis was done on a 19-year-old power plant in cold-dry climate to identify the most dominant failure and degradation modes. In addition, a comparison study was done on the current power plant (framed) along with another 18-year-old (frameless) from the same climate zone to understand the failure modes for cold-dry climatic condition.

Contributors

Agent

Created

Date Created
  • 2015

154659-Thumbnail Image.png

Climate-specific degradation rate and linearity analysis of photovoltaic power plants using performance ratio, performance index, and raw kWh methods

Description

In the past 10 to 15 years, there has been a tremendous increase in the amount of photovoltaic (PV) modules being both manufactured and installed in the field. Power plants

In the past 10 to 15 years, there has been a tremendous increase in the amount of photovoltaic (PV) modules being both manufactured and installed in the field. Power plants in the hundreds of megawatts are continuously being turned online as the world turns toward greener and sustainable energy. Due to this fact and to calculate LCOE (levelized cost of energy), it is understandably becoming more important to comprehend the behavior of these systems as a whole by calculating two key data: the rate at which modules are degrading in the field; the trend (linear or nonlinear) in which the degradation is occurring. As opposed to periodical in field intrusive current-voltage (I-V) measurements, non-intrusive measurements are preferable to obtain these two key data since owners do not want to lose money by turning their systems off, as well as safety and breach of installer warranty terms. In order to understand the degradation behavior of PV systems, there is a need for highly accurate performance modeling. In this thesis 39 commercial PV power plants from the hot-dry climate of Arizona are analyzed to develop an understanding on the rate and trend of degradation seen by crystalline silicon PV modules. A total of three degradation rates were calculated for each power plant based on three methods: Performance Ratio (PR), Performance Index (PI), and raw kilowatt-hour. These methods were validated from in field I-V measurements obtained by Arizona State University Photovoltaic Reliability Lab (ASU-PRL). With the use of highly accurate performance models, the generated degradation rates may be used by the system owners to claim a warranty from PV module manufactures or other responsible parties.

Contributors

Agent

Created

Date Created
  • 2016

154956-Thumbnail Image.png

Defects and statistical degradation analysis of photovoltaic power plants

Description

As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV)

As the photovoltaic (PV) power plants age in the field, the PV modules degrade and generate visible and invisible defects. A defect and statistical degradation rate analysis of photovoltaic (PV) power plants is presented in two-part thesis. The first part of the thesis deals with the defect analysis and the second part of the thesis deals with the statistical degradation rate analysis. In the first part, a detailed analysis on the performance or financial risk related to each defect found in multiple PV power plants across various climatic regions of the USA is presented by assigning a risk priority number (RPN). The RPN for all the defects in each PV plant is determined based on two databases: degradation rate database; defect rate database. In this analysis it is determined that the RPN for each plant is dictated by the technology type (crystalline silicon or thin-film), climate and age. The PV modules aging between 3 and 19 years in four different climates of hot-dry, hot-humid, cold-dry and temperate are investigated in this study.

In the second part, a statistical degradation analysis is performed to determine if the degradation rates are linear or not in the power plants exposed in a hot-dry climate for the crystalline silicon technologies. This linearity degradation analysis is performed using the data obtained through two methods: current-voltage method; metered kWh method. For the current-voltage method, the annual power degradation data of hundreds of individual modules in six crystalline silicon power plants of different ages is used. For the metered kWh method, a residual plot analysis using Winters’ statistical method is performed for two crystalline silicon plants of different ages. The metered kWh data typically consists of the signal and noise components. Smoothers remove the noise component from the data by taking the average of the current and the previous observations. Once this is done, a residual plot analysis of the error component is performed to determine the noise was successfully separated from the data by proving the noise is random.

Contributors

Agent

Created

Date Created
  • 2016