Development of a sustainable non-intrusive monitoring framework for grid-connected photovoltaic systems

Abstract

This study assesses the implementation of an advanced, sustainable and non-intrusive monitoring system as a data-driven solution for photovoltaic (PV) asset management. The approach capitalizes on existing devices within PV systems, enabling both new and retrofit applications without disrupting operation, while remaining aligned with IEC 61724-1:2021 guidelines. A full year of operational data from two PV plants in southern Spain was analyzed, yielding high system-level Performance Ratios (PR) between 78.61 % and 86.70 %. The monitoring system provides the basis for developing fault diagnosis methodologies, quantification of energy losses and detection of operational deviations. The cost–benefit analysis is strongly dependent on plant size. In medium-scale systems (100 kW up to 1 MW), its relatively low cost (2.08 %) is outweighed by significant returns derived from improved reliability and enabling the implementation of early fault detection methodologies, while in small-scale systems, the higher proportional cost (30.5 %) remains a barrier to wider adoption. The economic evaluation, carried out on a 44.10 kWp array, classified as small-scale according to the proposed size categorization, shows a Net Present Value (NPV) of 2204.79 €, an Internal Rate of Return (IRR) of 9.96 % and a discounted payback period of 8.93 years, resulting in a cumulative net benefit of 4501.41 €. In medium-scale systems, where relative costs are lower, economic feasibility is expected to be even more favorable. Beyond profitability, the system provides high-resolution historical datasets that support preventive and predictive maintenance strategies, estimation of PV degradation and assessment of economic impacts of anomalies. This hybrid Class A/B-compliant monitoring framework enables energy forecasting, adaptive control and enhanced grid integration, thus fostering both technical and economic sustainability of PV assets.The work was supported by the projects oriented towards the ecological transition and the digital transition. (Grant No. TED2021-131137B-I00 (“Aportación a la Transición Ecológica en el sector Industrial a través del Autoconsumo Fotovoltaico”) and “Centro para el Desarrollo Tecnológico Industrial (CDTI)” and “Corporación Tecnológica de Andalucía (CTA)” under the project: “SolAGRO + . Análisis funcional avanzado predictivo para la mejora de la gestión del mantenimiento de sistemas de autoconsumo solar fotovoltaico en sector de la industria agroalimentaria. Funding for open access charge: Universidad de Jaén/CBUA. The authors also acknowledge the support provided by the Thematic Network 723RT0150 “Red para la integración a gran escala de energías renovables en sistemas electricos (RIBIERSE-CYTED)” financed by the call for Thematic Networks of the CYTED (Ibero American Program of Science and Technology for Development) for 2022. The authors would like to thank the University of Jaén for its support by the programme: “Acción 2. Doctorados en entidades externas comprendida en la “Línea de Actuación: Fomento y divulgación de la transferencia”, enmarcada en el Objetivo 1: “Apoyo a las actividades de trasferencia del conocimiento”, del Plan de Apoyo a la Transferencia del Conocimiento, el Emprendimiento y la Empleabilidad año 2023, para la contratación de doctorandos industriales”