Abstract
The availability of information about solar radiation characteristics, particularly solar radiation predictions, is important for efficiently designing solar energy systems. Solar radiation information available in Saudi Arabia with this study, a new two-step artificial neural network (ANN), is proposed to estimate both the daily average and hourly solar radiation at Farasan Island, KSA (Kingdom of Saudi Arabia). The input parameters for the daily average solar radiation estimation are the location and time required, along with five selected monthly meteorological parameters that predict for the subsequent month. The selected meteorological parameters are temperatures, relative humidity, and precipitation. These three selected meteorological parameters (temperatures, relative humidity, and precipitation) are used them for measurement. The accuracy of the proposed method is comparable to previous studies with an average R2 of 96.80% for the daily average solar radiation estimate and 94.33% for the hourly solar radiation estimate.
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Singh, A.K., Pandey, V., Pachauri, R.K. (2021). Estimation of Solar Radiation at Farasan Island with Two-Step ANN Concepts. In: Choudhury, S., Gowri, R., Sena Paul, B., Do, DT. (eds) Intelligent Communication, Control and Devices. Advances in Intelligent Systems and Computing, vol 1341. Springer, Singapore. https://doi.org/10.1007/978-981-16-1510-8_15
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