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ARIMA and regression models for prediction of daily and monthly clearness index

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  • Hassan, Jamal

Abstract

Hourly and daily measurements of total and diffuse solar radiation and sunshine duration are analyzed. Three-year measurements of the available meteorological data in Mosul (latitude 36° 19′ N, longitude 43° 09′ E and 223 m above mean sea level) are used in this study. The present work involves two parts; in the first one, monthly mean daily and hourly of total and diffuse solar radiation are analyzed. The results show that the annual mean of the daily total and diffuse solar radiation is 5.11 and 1.6 kWh/m2 respectively. 57% of the days of the year are clear, while only 11.5% of the days are cloudy. Several empirical equations for estimating monthly mean daily global and diffuse solar radiation have been developed and compared with other available models. Ratio of average hourly to daily total solar radiation, for each month of the year is studied and compared with the theoretical results. In the second part, time-series model building using Box–Jenkins procedure to the daily clearness index is performed. The ARIMA(2,1,1) is developed for predication of daily clearness index.

Suggested Citation

  • Hassan, Jamal, 2014. "ARIMA and regression models for prediction of daily and monthly clearness index," Renewable Energy, Elsevier, vol. 68(C), pages 421-427.
  • Handle: RePEc:eee:renene:v:68:y:2014:i:c:p:421-427
    DOI: 10.1016/j.renene.2014.02.016
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    Cited by:

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    2. Rivero, M. & Orozco, S. & Sellschopp, F.S. & Loera-Palomo, R., 2017. "A new methodology to extend the validity of the Hargreaves-Samani model to estimate global solar radiation in different climates: Case study Mexico," Renewable Energy, Elsevier, vol. 114(PB), pages 1340-1352.
    3. Ahmed, Eihab E.E. & Demirci, Alpaslan & Tercan, Said Mirza, 2023. "Optimal sizing and techno-enviro-economic feasibility assessment of solar tracker-based hybrid energy systems for rural electrification in Sudan," Renewable Energy, Elsevier, vol. 205(C), pages 1057-1070.
    4. Ntumba Marc-Alain Mutombo & Bubele Papy Numbi, 2022. "The Development of ARIMA Models for the Clear Sky Beam and Diffuse Optical Depths for HVAC Systems Design Using RTSM: A Case Study of the Umlazi Township Area, South Africa," Sustainability, MDPI, vol. 14(6), pages 1-16, March.
    5. Martins, Guilherme Santos & Giesbrecht, Mateus, 2021. "Clearness index forecasting: A comparative study between a stochastic realization method and a machine learning algorithm," Renewable Energy, Elsevier, vol. 180(C), pages 787-805.
    6. Mohammad Mahdi Forootan & Iman Larki & Rahim Zahedi & Abolfazl Ahmadi, 2022. "Machine Learning and Deep Learning in Energy Systems: A Review," Sustainability, MDPI, vol. 14(8), pages 1-49, April.
    7. Brahim Belmahdi & Mohamed Louzazni & Mousa Marzband & Abdelmajid El Bouardi, 2023. "Global Solar Radiation Forecasting Based on Hybrid Model with Combinations of Meteorological Parameters: Morocco Case Study," Forecasting, MDPI, vol. 5(1), pages 1-24, January.
    8. Gairaa, Kacem & Khellaf, Abdallah & Messlem, Youcef & Chellali, Farouk, 2016. "Estimation of the daily global solar radiation based on Box–Jenkins and ANN models: A combined approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 238-249.
    9. Hussain, Sajid & Al-Alili, Ali, 2016. "A new approach for model validation in solar radiation using wavelet, phase and frequency coherence analysis," Applied Energy, Elsevier, vol. 164(C), pages 639-649.

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