Randomized trial analyzes energy production in photovoltaic systems, suggesting maintenance priorities for efficiency.
Conventional photovoltaic performance indicators provide useful benchmarking but do not determine whether production deficits arise from expected weather and module effects or from unresolved plant-side behaviour. This study develops a residual performance diagnostic framework for data-limited grid-connected photovoltaic plants and applies it to two adjacent fixed-tilt crystalline-silicon systems, each rated at 99.36 kWp, in South Corfu, Greece, over 2016–2023. An expected-energy baseline was constructed using hourly irradiance and meteorological data from the Photovoltaic Geographical Information System after explicit correction for incidence-angle effects, irradiance-level response, module temperature, and first-order air-mass and spectral effects. Measured alternating-current energy delivered to the grid, obtained from the Hellenic Electricity Distribution Network Operator, was then compared with the corrected expected energy through a weather-adjusted system-efficiency indicator and its complementary residual-loss coefficient. The explicit module and weather loss envelope remained close to 9.01%, with temperature as the largest modelled component. Residual losses increased from 10.76% to 14.53% in Plant 1 and from 10.51% to 16.26% in Plant 2. The fitted apparent annual declines were 0.453 percentage points per year for Plant 1 and 0.609 percentage points per year for Plant 2. A generation-hour uncertainty analysis based on independent observations from the Hellenic National Meteorological Service gave expanded uncertainties of ±5.80% for expected energy and ±5.89% for the system-efficiency indicator. The framework is therefore presented as an uncertainty-bounded screening method for prioritizing inspection and maintenance, not as a root-cause diagnostic or a formal performance-loss-rate assessment.
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Giannadakis et al. (2026) studied this question.
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