Quantitative Risk Assessment of Hourly Solar Radiation Forecasting using Monte Carlo Method: A Comparative Stability Study of CPR Model in Thailand
Keywords:
Monte Carlo Simulation, Hourly Solar Radiation, CPR Model, Risk AnalysisAbstract
Efficient management of solar energy systems requires accurate hourly global solar radiation data. This study aimed to analyze quantitative risk and establish confidence intervals for solar radiation forecasting using the Collares-Pereira and Rabl (CPR) model. The study applied Monte Carlo Simulation with 10,000 iterations, based on the Normal Distribution Assumption, utilizing Root Mean Square Difference (RMSD) and Mean Bias Difference (MBD) statistics from standard measurement stations in Chiang Mai and Ubon Ratchathani. The results indicated that while the mean forecast values for both stations were similar, the 95% confidence interval width for Ubon Ratchathani was 49.8% wider than that of Chiang Mai. Furthermore, the probability of error exceeding 10% in Ubon Ratchathani was three times higher. These findings suggested that solar system design in the Northeastern region required a higher safety margin compared to the Northern region to accommodate significantly higher uncertainty fluctuations. However, these results relied on the error distribution assumption, which should be further investigated in future research.
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