Review, challenges, and scope of advancements in outdoor quantitative electroluminescence imaging for solar PV

Qualitative electroluminescence (EL) imaging is a prominent tool for inspecting defective photovoltaic (PV) modules in outdoor installations. While the qualitative approach has proven valuable, the developing field of quantitative EL imaging offers significant advantages by enabling a deeper evaluation of module performance from EL images. Most research on quantitative EL imaging has been conducted under controlled indoor conditions, and the literature lacks an in-depth discussion on its adaptation for outdoor PV installations. This article aims to bridge that gap by reviewing various quantitative EL approaches and examining the challenges associated with their application in PV installations. Progress in EL imaging technology is presented across key implementation aspects. Major focus is given on quantitative EL approaches, such as parametric extraction, machine learning, empirical methods, and multi-characterization techniques. A comparative assessment of these approaches is conducted, emphasizing their requirements for outdoor EL inspections, including minimum EL data acquisition needs, ease of outdoor implementation, and the capability to extract cell-level or module-level quantitative information. Based on this assessment, the applicability and potential challenges of each approach are analyzed for different PV installations, along with strategies for overcoming these challenges. Furthermore, the scope of advancements in EL data acquisition, EL software, and EL standards is outlined.