2020 PV Reliability Workshop: February 27, 2020 Proceedings
These are the proceedings from the Feb. 27, 2020 Photovoltaic Reliability Workshop (PVRW) 2020 Conference.
41 EE - Solar Energy Technologies Office (EE-4S)↗
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2020 PV Reliability Workshop: February 26, 2020 Proceedings
These are the proceedings from the Feb. 26, 2020 Photovoltaic Reliability Workshop (PVRW) 2020 Conference.
41 EE - Solar Energy Technologies Office (EE-4S)↗
2020 PV Reliability Workshop: February 25, 2020 Proceedings
These are the proceedings from the Feb. 25, 2020 Photovoltaic Reliability Workshop (PVRW) 2020 Conference.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Proceedings of the PV Reliability Workshop, February 21-25, 2022
The 2022 PV Reliability Workshop (PVRW) was held virtually from February 21-25, 2022. These proceedings collect the oral and poster presentation recordings from the workshop.
photovoltaics↗
AI and ML Applications for PV Reliability and System Performance
This poster discusses AI and ML topics in PV reliability and system performance. In particular, automated metadata extraction and QA for fielded solar installations is covered for the PV Fleets Project. Additionally, statistical learning topics for the PVInsight Project are addressed, as well as development of the PV Validation Hub.
algorithm↗
Energy in the Balance: PV Reliability to Power the Energy Transition
We present an analysis of the effects of reliability on our ability to achieve the energy transition deployment targets. We examine three end of life modes as captured in the PV ICE tool; degradation, failures, and project lifetime. Recommendations are made for improving PV reliability for achieving energy energy transition.
circularity↗
PV Reliability and Resilience in Challenging Climates
Challenging climates for Photovoltaics are usually based on climate classification. However, extreme weather events such as high wind, flooding, large hail, extreme snow etc. have become more ubiquitous globally. To study the impact of extraordinary weather events on PV reliability we used two of the largest databases in the USA. First, the National Oceanic and Atmospheric Administration (NOAA) database on extreme weather and secondly, the PV Fleet Data Initiative where we have collected high-resolution PV performance data of more than 8 gigawatts or about 6-7% of all commercial and utility systems in the USA. We analyzed almost 200 systems between 2008-20022 that were immediately impacted by these weather events. The immediate impact (outages) was determined to be about 1% of or a median of approximately 3 days of annual lost production. However, the risk these events pose is exemplified by a long tail where 0.4 % of all systems lost more than 2 weeks annual production. We also found a threshold for high wind (90 km/hr) and hail (25mm), above which we observed significantly higher degradation implying long-term damage to the systems. In addition, we are using satellite imagery to quantify visible damage to PV plants. Finally, we share module, design and installation lessons from some observed case studies to improve extreme weather resilience for PV power systems.
degradation↗
PV Reliability Lessons from 100,000 Systems
Despite the importance of reliability to the cost competitiveness of PV, large data sets enabling high-level investigation of the technology’s performance in the field are relatively scarce. Dirk C. Jordan, Chris Deline, Bill Marion and Teresa Barnes of the National Renewable Energy Laboratory, and Mark Bolinger of the Lawrence Berkeley National Laboratory study a unique data set of 100,000 PV systems in the US, drawing out tips for better reliability that have relevance to other parts of the world.
41 EE - Solar Energy Technologies Office (EE-4S)↗
Proceedings of the PV Reliability Workshop, February 22-26, 2021
The 2021 Photovoltaic Reliability Workshop (PVRW) continued in the longstanding PVRW tradition of engaged, passionate presentation and discussion, though in a new virtual format for 2021. The workshop was hosted over 5 days, with each day featuring two oral presentation sessions and one interactive poster session. In these proceedings, you will find links to video recordings for most of the oral presentations and poster presentations along with Q&A sessions and panel discussions. Each presentation is linked from its title in this agenda.
41 EE - Solar Energy Technologies Office (EE-4S)↗
PV Reliability Development Lessons from JPL's Flat Plate Solar Array Project
No abstract available
flat plate solar arrays project↗
PV Reliability Development Lessons from JPL's Flat Plate Solar Array Project
Key reliability and engineering lessons learned from the 20-year history of the Jet Propulsion Laboratory's Flat-Plate Solar Array Project and thin film module reliability research activities are presented and analyzed. Particular emphasis is placed on lessons applicable to evolving new module technologies and the organizations involved with these technologies. The user-specific demand for reliability is a strong function of the application, its location, and its expected duration. Lessons relative to effective means of specifying reliability are described, and commonly used test requirements are assessed from the standpoint of which are the most troublesome to pass, and which correlate best with field experience. Module design lessons are also summarized, including the significance of the most frequently encountered failure mechanisms and the role of encapsulate and cell reliability in determining module reliability. Lessons pertaining to research, design, and test approaches include the historical role and usefulness of qualification tests and field tests.
photovoltaics↗
Enhancing PV Inverter Reliability Through Predictive Maintenance: Insights from Retrofitting of PV Inverters
Photovoltaic (PV) systems represent a cornerstone in the global shift toward sustainable energy generation, with inverters serving as the crucial link between solar panels and the grid. Despite their pivotal role, inverters are susceptible to failures, contributing significantly to maintenance events and operational disruptions in large-scale PV plants. This white paper investigates the importance and methodologies of predictive maintenance strategies that monitor the component-level pre-failure signatures on PV inverters. Through a comprehensive survey of literature and industry professionals, insights on preventive maintenance and retrofitting practices have been gathered. The expert elicitation helps shed light on common challenges and opportunities for improving PV system reliability, particularly inverter reliability. By addressing these challenges, the white paper aims to enhance the long-term viability and effectiveness of solar PV plants in the renewable energy landscape, contributing to the global transition toward environmentally friendly energy generation.
14 SOLAR ENERGY↗
Photovoltaics module reliability for the terawatt age
Photovoltaics (PV), or solar electricity generation, has become the cheapest form of energy in many locations worldwide and, combined with energy storage, has the potential to satisfy most of our electricity needs. PV has grown at an annual compounded growth rate of approximately 30% in the last three decades. Solar energy systems will continue their impressive growth in distributed energy, microgrids, and utility scale, as efforts are made for dependable electricity in an age with increasing extreme weather. However, within this remarkable success lies a new challenge. The growth curve, combined with rapid product innovation and scale up, means that the majority of PV systems are new, without the three years of performance data that have been required in the past to estimate product lifetime. PV reliability has to address this challenge. In this review we present a brief summary of PV reliability starting with brief historical synopsis, detailing some of the technological challenges and present a framework required for long lifetime.
14 SOLAR ENERGY↗
Accelerating Simulation for High-Fidelity PV Inverter System Reliability Assessment with High-Performance Computing
The overall cost of photovoltaic (PV) systems has shown a downward trend during the last decade; however, PV inverter failures account for the highest cost of operation and maintenance. To address this, reliability tools with powerful computation and better accuracy are required for the lifetime prediction and degradation evaluation of PV inverters. This paper proposes an event-driven parallel computing-based simulator. The proposed simulator applies high-performance computing techniques and other accessory optimization techniques-including cluster merging, adaptive model updates, and steady-state identification-to make reliability assessments for PV inverters under given input mission profiles and operating conditions with high efficiency and high fidelity. The main idea of the simulator and its workflow are introduced. Then, a demo PV inverter system simulator is implemented, and the speedup of the total simulations of the switching model reaches 123.03 times.
high-performance computing↗
Photovoltaics Research at NREL
General overview of NREL research, including scaling to terawatt PV, reliability testing, DuraMAT, perovskites, silicon PV, CdTe, III-V, and tandems.
CdTe↗
Integrated Approach to Ancillary PV Component Reliability Assessment (Final Report)
In this project, we have established a nondestructive, generalized methodology that (1) fuses rich field data with advanced ML for proactive reliability forecasting, (2) dramatically reduces experimental iterations via synthetic dataset generation, and (3) achieves unprecedented regression precision in both anomaly detection and component-level degradation assessment—paving the way for truly predictive maintenance of grid-tied PV inverters under diverse outdoor conditions.
14 SOLAR ENERGY↗
Design and Implementation of Automated Characterization of T-type based Power Module for PV Inverter Reliability Assessment
Reliability of power electronics holds the key for future power and energy systems since it is essential for system integration with renewables and energy storage systems. Variation of power module characteristics over the converter’s operational lifetime is a critical indicator to assess its reliability. Device characterization consists of different steps to collect, process, and visualize results, which is usually time-consuming, especially for power modules based on a non-phase-leg configuration, such as T-type circuits, widely applied for PV inverters. To reduce the time, ensure repeatability, and guarantee consistency, an automated test bench can be helpful. This paper focuses on a T-type-based power module and proposes a unique characterization platform and corresponding automation procedure and implementation. Considering the major characterization difference between T-type power modules over the conventional phase-leg power module, first, the special consideration for static characterization is highlighted. Second, the unique dynamic characterization design associated with the T-type power module is described. Finally, the automation of the power module characterization and the test platform is presented along with results and special considerations.
Siraj, Ahmed↗