Forecasting Electricity Demand for Turkey Using Modulated Fourier Expansion
Keywords:
Time series analysis, Fourier series, Hourly electricity demand for Turkey, deregulated electricity market, load forecast.Abstract
Turkish power market has undergone a restructuring and deregulation to reach a competitive and reliable electricity market. A typical day starts when the system operator announces the next day demand forecast for the electricity and participants submit offers in response to meet the demand. Accuracy in electricity demand forecast is essential for a reliable power system and successful market operation and mathematical models help market participants to forecast the electricity demand. We use hourly electricity demand data for Turkey, for the years 2012-2014 to make a linear model taking into account weekly and diurnal periodic variations modulated by seasonal effects. The model fits the data within %4 and predicts within %9.8 in the L2 norm.References
[1] I. Dyner, E. Larsen. “From planning to strategy in the electricity industry.” Energy Policy. Vol. 29(13):, pp. 1145-1154, 2001.
[2] JV Ringwood, D. Bofelli., F.T. Murray “Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks.” Journal of Intelligent and Robotic Systems. vol.31, pp. 129-147, 2001.
[3] SR Brubacher, GT Wilson. “Interpolating time series with application to the estimation of holiday effects on electricity demand.” Applied Statistics, vol. 25(2), pp. 107-116, 1976.
[4] C Crowley, FL Joutz, “Hourly Electricity Loads: Temperature Elasticities and Climate Change”, 23rd US Association of Energy Economics North American Conference, Mexico City October 19-21, 2003.
[5] AC Toker,O Korkmaz, “Türkiye K?sa Süreli Elektrik Talebinin Saatlik Olarak Tahmin Edilmesi.”, Aplus Enerji, Istanbul,Turkey, 2010.
[6] JW Taylora, R Buizzab, “Using weather ensemble predictions in electricity demand forecasting.”, International Journal of Forecasting , vol.19(1), pp. 57-70, 2003.
[2] JV Ringwood, D. Bofelli., F.T. Murray “Forecasting Electricity Demand on Short, Medium and Long Time Scales Using Neural Networks.” Journal of Intelligent and Robotic Systems. vol.31, pp. 129-147, 2001.
[3] SR Brubacher, GT Wilson. “Interpolating time series with application to the estimation of holiday effects on electricity demand.” Applied Statistics, vol. 25(2), pp. 107-116, 1976.
[4] C Crowley, FL Joutz, “Hourly Electricity Loads: Temperature Elasticities and Climate Change”, 23rd US Association of Energy Economics North American Conference, Mexico City October 19-21, 2003.
[5] AC Toker,O Korkmaz, “Türkiye K?sa Süreli Elektrik Talebinin Saatlik Olarak Tahmin Edilmesi.”, Aplus Enerji, Istanbul,Turkey, 2010.
[6] JW Taylora, R Buizzab, “Using weather ensemble predictions in electricity demand forecasting.”, International Journal of Forecasting , vol.19(1), pp. 57-70, 2003.
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Published
2015-11-27
How to Cite
Yucekaya, A., Yukseltan, E., & Bilge, A. H. (2015). Forecasting Electricity Demand for Turkey Using Modulated Fourier Expansion. American Scientific Research Journal for Engineering, Technology, and Sciences, 14(3), 87–94. Retrieved from https://asrjetsjournal.org/index.php/American_Scientific_Journal/article/view/1142
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