Network Models of Active Degradation Mechanisms and Pathways for Service Life Prediction of Indoor and Outdoor PV Modules

• DOI: 10.2172/1900601
• Publication Date: 2022-12-14T03:13:06Z
• Authors: Roger French; Laura Bruckman; Sameera Nalin Venkat; Jiqi Liu; Kristen Hernandez; Xuanji Yu; Jayvic Jimenez; Karl-Anders Weiss; Kaushik Choudhury; Xinjin Li; Jean-Nicolas Jaubert

ct: PV service lifetime prediction (SLP) enables accurate calculation of levelized cost energy (LCOE), which is crucial to rationalizing investment and installation. However, SLP challeging since reliability in the field affected by many combined factors, including various environmental stresses module quality. In order map out active degradation mechanisms pathways that best resemble real world conditions, we introduce framework a study protocol use network models fitted data, enable analysis complex systems with multiple mechanisms. The experimental design, variants different exposure selection evaluation methods, time-series data acquisition training these data. We present minimodules lab field. For SLP, 8 based on manufacturer, architecture, encapsulation were prepared aged modified damp heat or without full spectrum light exposure. Stepwise I-V Suns-Voc tracks changes electrical properties Rs,IV, Isc,IV, Vmp,PIV providing insights into power loss minimodules. Network structural equation modeling (netSEM) was utilized construct pathway identify predict over time. datastreams Pmp values curve two types modules installed three distinctly Köppen-Geiger climate zones for 9 years acquired. With modes corresponding uniform current (ΔPIsc), recombination (ΔPVoc), series resistance (ΔPRs), mismatch (ΔPImis) determined, performance rates (PLR) determined using PVplr. show how establish ensure appropriate parametric variations valid collection from your systems. Then data-driven netSEM model fitting provides comprehensive mapping mechanisms, life prediction.