Abstract
Solar energy does not always follow the normal distribution due to the characteristics of natural energy. The system advisor model (SAM), a well-known energy performance analysis program, analyzes exceedance probabilities by dividing solar irradiance into two cases, i.e., when normal distribution is followed, and when normal distribution is not followed. However, it does not provide a mathematical model for data distribution when not following the normal distribution. The present study applied the skew-normal distribution when solar irradiance does not follow the normal distribution, and calculated photovoltaic power potential to compare the result with those using the two existing methods. It determined which distribution was more appropriate between normal and skew-normal distributions using the Jarque–Bera test, and then the corrected Akaike information criterion (AICc). As a result, three places in Korea showed that the skew-normal distribution was more appropriate than the normal distribution during the summer and winter seasons. The AICc relative likelihood between two models was more than 0.3, which showed that the difference between the two models was not extremely high. However, considering that the proportion of uncertainty of solar irradiance in photovoltaic projects was 5% to 17%, more accurate models need to be chosen.
Highlights
The variation of annual performance in solar energy systems is the essential factor considered in a project’s economic feasibility [1]
The lowest power which haswas been widely used as a performance program inisexisting solar energy systems, potential produced in winter
It is inferredsimulation that the main reason the high temperature of Jeju the normal distribution assumed for annual data, and temperatures the P50/P90 values
Summary
The variation of annual performance in solar energy systems is the essential factor considered in a project’s economic feasibility [1]. The risk evaluation of P50/P90 is mainly used to evaluate the economic feasibility of wind farm projects. Since solar irradiance is a more predictable resource than wind velocity, it can be applied to risk evaluations of photovoltaic (PV) or concentrated solar thermal power projects [2,3]. P50 means that the predicted solar resource/energy yield may either be exceeded or not be exceeded, with a 50% probability of either occurring. The P90 value is expected to be exceeded in 90%. In the PV power generation system, a P50 value of 30,000 kWh means the system output may exceed 30,000 kWh with a probability of 50%.
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