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

• Monitoring improves PV reliability by early detection of suboptimal performance. • Data-driven approach quantifies energy losses and operational deviations in PV plants. • Cost–benefit analysis shows positive NPV (2204.79€) and IRR (11.96 %) for monitoring. • Scalable approach: higher returns in medium-scale PV systems with low relative cost. • Enables transition to predictive maintenance, enhancing plant availability and lifespan. 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.