Predictive Modeling for Assessing the Reliability of Bypass Diodes in Photovoltaic Modules

Solar Photovoltaics (PV) is one of the most promising renewable energy technologies for mitigating the effect of climate change. Reliability of PV modules directly impacts the Levelized Cost of Energy (LCOE), which is a metric for cost competitiveness of any energy technology. Further reduction in LCOE of PV through assured long term reliability is necessary in order to facilitate widespread use of solar energy without the need for subsidies. This dissertation is focused on frameworks for assessing reliability of bypass diodes in PV modules. Bypass diodes are critical components in PV modules that provide protection against shading. Failure of bypass diode in short circuit results in reducing the PV module power by one third, while diode failure in open circuit leaves the module susceptible for extreme hotspot heating and potentially fire hazard. PV modules, along with the bypass diodes are expected to last at least 25 years in field. The various failure mechanisms in bypass diodes such as thermal runaway, high temperature forward bias operation and thermal cycling are discussed. Operation of bypass diode under shading is modeled and method for calculating the module I-V curve under any shading scenario is presented. Frameworks for estimating the diode temperature in field deployed modules based on Typical Meteorological Year (TMY) data are developed. Model for predicting the susceptibility of bypass diodes for thermal runaway is presented. Diode wear out due to High Temperature Forward Bias (HTFB) operation and Thermal Cycling (TC) is studied under custom designed accelerated tests. Overall, this dissertation is an effort towards estimating the lifetime of bypass diodes in field deployed modules, and therefore, reducing the uncertainty in long term reliability of PV modules.

Author dc:creator

• Shiradkar, Narendra

Contributors dc:contributor

• Sundaram, Kalpathy B.

• Pv module
• reliability
• bypass diode
• accelerated test
• photovoltaics
• Electrical and Computer Engineering
• Electrical and Electronics
• Engineering
• Dissertations, Academic -- Engineering and Computer Science; Engineering and Computer Science -- Dissertations, Academic

Language dc:language

English

Identifier

CFE0006001

OAI identifier oai:identifier

oai:stars.library.ucf.edu:etd-2400