An interest in floating photovoltaic (PV) is growing drastically worldwide. To evaluate the feasibility of floating PV projects, an accurate estimation of electric power output (EPO) is a crucial first step. This study estimates the EPO of a floating PV system and compares it with the actual EPO observed at the Hapcheon Dam, Korea. Typical meteorological year data and system design parameters were entered into System Advisor Model (SAM) software to estimate the hourly and monthly EPOs. The monthly estimated EPOs were lower than the monthly observed EPOs. This result is ascribed to the cooling effect of the water environment on the floating PV module, which makes the floating PV efficiency higher than overland PV efficiency. Unfortunately, most commercial PV software, including the SAM, was unable to consider this effect in estimating EPO. The error results showed it was possible to estimate the monthly EPOs with an error of less than 15% (simply by simulation) and 9% (when considering the cooling effect: 110% of the estimated monthly EPOs). This indicates that the approach of using empirical results can provide more reliable estimation of EPO in the feasibility assessment stage of floating PV projects. Furthermore, it is necessary to develop simulation software dedicated to the floating PV system.

In this study, the photovoltaic (PV) potential was predicted and verified with the observed values of the fixed floating PV system at Hapcheon Dam. The observed power outputs from the fixed and tracking floating PV systems were compared. The System Advisor Model software was used to analyze the meteorological data of the study area and system design specifications. For the fixed PV system, the observed values were generally higher than the predicted values. Based on the difference between the observed and predicted values of monthly power output, the calculated mean absolute percentage error (MAPE) was 14%. According to a previous study in which the amount of power output on the water was approximately 5%-10% higher than that on the on-land system, the monthly MAPE would be approximately 11%, and the annual error rate would be approximately 2%. In addition, the tracking PV system showed a slightly higher monthly power output than the fixed PV. It is expected that the proposed system will yield improved accuracy in the renewable energy output prediction system with the power output prediction algorithm for floating PV systems.

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