THERMAL SCIENCE

International Scientific Journal

Authors of this Paper

External Links

TIME DEPENDENT PREDICTION OF MONTHLY GLOBAL SOLAR RADIATION AND SUNSHINE DURATION USING EXPONENTIALLY WEIGHTED MOVING AVERAGE IN SOUTHEASTERN OF TURKEY

ABSTRACT
This paper proposes a new approach for prediction of Global Solar Radiation and Sunshine Duration based on earlier years of data for the eastern region of Turkey which has a high potential of solar energy. The proposed method predicts the basic parameters using time series and an analysis method. This method is Exponentially Weighted Moving Average (EWMA). This model estimates next years’ Global Solar Radiation and Sunshine Duration and is evaluated by statistical parameters, Mean Absolute Percentage Error (MAPE) and Coefficient of Determination, (R2) to examine the success of the proposed technique. In our study, the result shows that this method is effective in predicting Global Solar Radiation and Sunshine Duration as regards of MAPE and R2. The calculated MAPEs which are between 0 - 10 kWh/m2 per day were assumed excellent and R2s were found significant per every year.
KEYWORDS
PAPER SUBMITTED: 2016-01-07
PAPER REVISED: 2016-08-06
PAPER ACCEPTED: 2016-09-20
PUBLISHED ONLINE: 2016-10-01
DOI REFERENCE: https://doi.org/10.2298/TSCI160107228K
CITATION EXPORT: view in browser or download as text file
THERMAL SCIENCE YEAR 2018, VOLUME 22, ISSUE Issue 2, PAGES [943 - 951]
REFERENCES
  1. Pierro, M., et al., Model Output Statistics Cascade to Improve Day Ahead Solar Irradiance Forecast, Sol. Energy, 117 (2015), July, pp. 99-113
  2. Petrovic, I., et al., Advanced PV Plant Planning based on Measured Energy Production Results – Approach and Measured Data Processing, Adv. Electr. Comput. Eng., 14 (2014), 1, pp. 49-54
  3. Yadav, A. K., Chandel, S. S., Solar Radiation Prediction Using Artificial Neural Network Techniques: A Review, Renew. Sustain. Energy Rev., 33 (2014), May, pp. 772-781
  4. Ravichandra, S., Rathnaraj, J. D., Analysis of Ratio of Global to Extra-Terrestrial Radiation (Clearness Index) at some Tropical Locations in India, Thermal Science, 21 (2017), 3, pp. 1379-1387
  5. Nazaripouya, H., et al., Univariate Time Series Prediction of Solar Power Using a Hybrid Wavelet-ARMA-NARX Prediction Method, IEEE PES T&D, Dallas, Tex., USA, 2016
  6. Shamim, M. A., et al., An Improved Technique for Global Solar Radiation Estimation Using Numerical Weather Prediction, J. Atmos. Solar-Terrestrial Phys., 129 (2015), July, pp. 13-22
  7. Adeyemi, A., et al., Evaluation of Global Solar Radiation Using Multiple Weather Parameters as Predictors for South Africa Provinces, Thermal Science, 19 (2015), Suppl. 2, pp. S495-S509
  8. Bakirci, K., Models for the Estimation of Diffuse Solar Radiation for Typical Cities in Turkey, Energy, 82 (2015), Mar., pp. 827-838
  9. Besharat, F., et al., Empirical Models for Estimating Global Solar Radiation: A Review and Case Study, Renew. Sustain. Energy Rev., 21 (2013), May, pp. 798-821
  10. Qazi, A., et al., The Artificial Neural Network for Solar Radiation Prediction and Designing Solar Systems: A Systematic Literature Review, J. Clean. Prod., 104 (2015), Oct., pp. 1-12
  11. McCandless, T. C., et al., A Model Tree Approach to Forecasting Solar Irradiance Variability, Sol. Energy, 120 (2015), Oct., pp. 514-524
  12. Shukla, K. N., et al., Comparative Study of Isotropic and Anisotropic Sky Models to Estimate Solar Radiation Incident on Tilted Surface: A Case Study for Bhopal, India, Energy Reports, 1 (2015), Nov., pp. 96-103
  13. Kisi, O., Modeling Solar Radiation of Mediterranean Region in Turkey by Using Fuzzy Genetic Approach, Energy, 64 (2014), Jan., pp. 429-436
  14. Guclu, Y. S., et al., Solar Irradiation Estimations and Comparisons by Anfis, Angstrom-Prescott and Dependency Models, Sol. Energy, 109 (2014), Nov., pp. 118-124
  15. Guclu, Y. S., et al., HARmonic-LINear (HarLin) Model for Solar Irradiation Estimation, Renew. Energy, 81 (2015), Sept., pp. 209-218
  16. Gerek, O. N., et al., Harmonic Analysis Based Hourly Solar Radiation Forecasting Model, IET Renew. Power Gener., 9 (2015), 3, pp. 218-227
  17. Park, J.-K., et al., A New Approach to Estimate the Spatial Distribution of Solar Radiation Using Topographic Factor and Sunshine Duration in South Korea, Energy Convers. Manag., 101 (2015), Sept., pp. 30-39
  18. De Andrade, R. C., Tiba, C., Extreme Global Solar Irradiance Due to Cloud Enhancement in Northeastern Brazil, Renew. Energy, 86 (2015), Feb., pp. 1433-1441
  19. Teke, A., Yildirim, H. B., Estimating the Monthly Global Solar Radiation for Eastern Mediterranean Region, Energy Convers. Manag., 87 (2014), Nov., pp. 628-635
  20. Holt, C. C., Forecasting Seasonals and Trends by Exponentially Weighted Moving Averages, Int. J. Forecast., 20 (2014), 1, pp. 5-10
  21. Kentli, F., Yilmaz, M., Mathematical Modelling of Two-Axis Photovoltaic System with Improved Efficiency, Elektronika Ir Elektrotechnika, 21 (2015), 4, pp. 40-43
  22. Boland, J., Time-Series Analysis of Climatic Variables, Solar Energy, 55 (1995), 5, pp. 377-388
  23. Brockwell, P., Davis, R. A., Introduction to Time Series and Forecasting, Springer-Verlag, New York, USA, 1996
  24. Bowerman, B. L., O’Connell, R. T., Time Series Forecasting, Duxbury Press, Boston, Mass., USA, 1979

© 2024 Society of Thermal Engineers of Serbia. Published by the Vinča Institute of Nuclear Sciences, National Institute of the Republic of Serbia, Belgrade, Serbia. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International licence