Operation and Maintenance Decision Support System for Photovoltaic Systems

Abstract

Operation and maintenance (O&M) and monitoring strategies are important for safeguarding optimum photovoltaic (PV) performance while also minimizing downtimes due to faults. An O&M decision support system (DSS) was developed in this work for providing recommendations of actionable decisions to resolve fault and performance loss events. The proposed DSS operates entirely on raw field measurements and incorporates technical asset and financial management features. Historical measurements from a largescale PV system installed in Greece were used for the benchmarking procedure. The results demonstrated the financial benefits of performing mitigation actions in case of near zero power production incidents. Stochastic simulations that consider component malfunctions and failures exhibited a net economic gain of approximately 4.17 €/kW/year when performing O&M actions. For an electricity price of 59.98 €/MWh, a minimum of 8.4% energy loss per year is required for offsetting the annualized O&M cost value of 7.45 €/kW/year calculated by the SunSpec/National Renewable Energy Laboratory (NREL) PV O&M Cost Model.

A comprehensive review of unmanned aerial vehicle-based approaches to support photovoltaic plant diagnosis

“…Electrical data characterisation methods include I–V curve analysis [ 93 , 94 ], signal analysis, circuit and simulation models [ 6 ]. Current trends and innovations in today's O&M market include the application of ML techniques [ 38 , 43 , 63 , 85 ] and data-driven decision making processes [ [95] , [96] , [97] , [98] ]. The number of ML-based research over the years for PV FDD is illustrated in Fig.…”

Field studies of PERC and Al-BSF PV module performance loss using power and I-V timeseries

“…The (Current-Voltage) I-V data collected at standard test conditions (STC) or in field were analyzed using open-source data analysis tools. We demonstrate that the data analysis pipeline is not only flexible enough to capture nonlinear performance degradation (Hashemi et al, 2020;French et al, 2021;Hashemi et al, 2021;Theristis et al, 2021;Lindig et al, 2022;Livera et al, 2022a), but also capable of extracting performance loss and changes in electrical features from I-V curves at outdoor conditions (Li et al, 2023;Meena et al, 2022;Jain et al, 2020;Livera et al, 2019). Furthermore, our pipeline can construct data-driven network models of degradation pathways, allowing for the comparison of degradation mechanism among different variants (Nalin Venkat et al, 2023).…”

Automated Fixing Cost Estimation of Photovoltaic System Failures for the Creation of a Decision Support System

“…The further progression of this tool is a fully automated DSS that presents for each identified failure in the field the most cost-effective solution or mitigation measures to apply. [11] Livera et al [12,13] proposed the optimization of O&M strategies through the implementation of a DSS for corrective maintenance of large-scale PV systems.…”