Open Data Sets for Assessing Photovoltaic Reliability

作者：Xin Chen, Baojie Li, Jennifer Lee Braid, Brandon Byford, Dylan J. Colvin, Andrew Glaws, Norman Jost, Benjamin C. Pierce, Salil Rabade, Martin S. Springer, Anubhav Jain · 年份：2024 · DOI：10.31224/4215 · 被引用次数：1 · 研究领域：Photovoltaic System Optimization Techniques、Energy and Environment Impacts、Solar Radiation and Photovoltaics

Photovoltaic (PV) systems have become a cornerstone of renewable energy strategies, particularly due to the significant reduction in solar power costs over the past decade. However, the long-term reliability of PV installations presents a persistent challenge, requiring the development of advanced monitoring and predictive maintenance strategies. A wide range of data types are used to evaluate the health of PV systems, including environmental conditions, electrical performance, and inspection imagery. These data enable methodologies such as machine learning (ML) models for lifetime prediction and computer vision techniques for defect detection. However, the acquisition of high-quality and comprehensive data is difficult, particularly in terms of long-term consistency and data variety. Publicly available data sets serve as valuable resources for addressing these challenges, but they often suffer from fragmentation and are difficult to access. This paper presents a comprehensive review of existing open-source data sets related to PV degradation, analyzing their features, functionalities, and potential applications. We categorize these data sets based on the specific aspects of PV system information they cover, such as environmental conditions, operational monitoring, and material inspection, and propose relevant tools and ML models for processing them. In addition, we propose practices for future data collection and usage, while also discussing potential directions in data-driv...