Hourly Electricity Load Forecasting: An Empirical Application to the Italian Railways

Authors: M. Centra

Abstract:

Due to the liberalization of countless electricity markets, load forecasting has become crucial to all public utilities for which electricity is a strategic variable. With the goal of contributing to the forecasting process inside public utilities, this paper addresses the issue of applying the Holt-Winters exponential smoothing technique and the time series analysis for forecasting the hourly electricity load curve of the Italian railways. The results of the analysis confirm the accuracy of the two models and therefore the relevance of forecasting inside public utilities.

Keywords: ARIMA models, Exponential smoothing, Electricity, Load forecasting, Rail transportation.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1082583

References:

[1] D.W. Bunn, and E.D. Farmer, (1985), Review of Short-Term Forecasting Methods in the Electricity Power Industry, New York: Wiley, 1985, pp. 13-30.
[2] T. Haida, and S. Muto, "Regression based peak load forecasting using a transformation technique", IEEE Trans. on Power Systems, vol. 9, p.p. 1788-1794, Issue: 4, 1994.
[3] P.D. Matthewman, and H.Nicholson, "Techniques for load prediction in electricity supply industry", Proceedings of the Institution of Electrical Engineers, vol. 115, p.p. 1451-1457, Issue: 10, 1968.
[4] M.A. Abu-E-Magd, and N.K. Sinha, "Short term load demand modeling and forecasting", IEEE Transactions on Systems Man and Cybernetics, vol. 12, p.p. 370-382, Issue: 3, 1982.
[5] G. Gross, and F.D. Galiana, "Short-term load forecasting", Proceedings of the IEEE, vol. 75, 1558-1573, Issue: 12, 1987.
[6] G.A. Darbellay, and M.Slama, "Forecasting the short-term demand for electricity - do neural networks stand a better chance?", International Journal of Forecasting, 16, p.p. 71-84, 2000.
[7] H.S. Hippert, C.E. Pedreira, and R.C. Souza, "Neural networks for shortterm load forecasting: a review and evaluation", IEEE Transactions on Power Systems, vol. 16, p.p. 44-55, Issue: 1, 2001.
[8] J.W. Taylor, L. de Menezes, and P.E. McSharry, "A comparison of univariate methods for forecasting electricity demand up to a day ahead, International Journal of Forecasting, 22(1), p.p. 1-16, 2006.
[9] M. Adya, and F. Collopy, "How effective are neural networks at forecasting and prediction? A review and evaluation", Journal of Forecasting, 17, pp. 481-495, 1998.
[10] S. Makridakis, S.C. Wheelwright, and R.J. Hyndman, Forecasting: Methods and Applications, Third Edition, New York: Wiley, 1998.
[11] G. Zhang, B.E. Patuwo, and M.Y. Hu, "Forecasting with artificial neural networks: the state of the art, International Journal of Forecasting, 14, p.p. 35-62, 1998.
[12] C.W. Gellings, Demand Forecasting for Electric Utilities, The Fairmont Press, Lilburn, GA, 1996.
[13] E.A. Feinberg, J.T. Hajagos, and D. Genethliou, "Load pocket modeling", Proceedings of the 2nd IASTED International Conference: Power and Energy Systems, p.p. 50-54, Crete, 2002.
[14] E.A. Feinberg, J.T. Hajagos, and D. Genethliou, "Statistical load modeling", Proceedings of the 7th IASTED International Conference: Power and Energy Systems, p.p. 88-91, Palm Springs, CA, 2003.
[15] R.F. Engle, C. Mustafa, and J. Rice, (1992), "Modeling peak electricity demand", Journal of Forecasting, vol. 11, p.p. 241-251, 1992.
[16] O. Hyde, and P.F. Hodnett, "Adaptable automated procedure for shortterm electricity load forecasting", IEEE Transactions on Power Systems, vo. 12, p.p. 84-94, Issue: 1, 1997.
[17] S. Ruzic, A. Vuckovic, and N. Nikolic, "Weather sensitive method for short-term load forecasting in electric power utility of Serbia", IEEE Transactions on Power Systems, vol. 18, p.p. 1581-1586, Issue: 18, 2003.
[18] T. Haida, S. Muto, Y. Takahashi, and Y. Ishi, "Peak load forecasting using multiple-year data with trend data processing techniques", Electrical Engineering in Japan, vol. 124, p.p. 7-16, Issue: 1, July 1998.
[19] W. Charytoniuk, M.S. Chen, and P. van Olinda, "Nonparametric regression based short-term load forecasting", IEEE Transactions on Power Systems, vol. 13, p.p. 725-730, Issue: 3, 1998.
[20] J.Y. Fan,. and J.D. McDonald, "A real-time implementation of short- Term load forecasting for distribution power system", IEEE Transactions on Power Systems, vol. 9, p.p. 988-994, Issue: 2, 1994.
[21] M.Y. Cho, J.C. Hwang, and C.S. Chen, "Customer short-term load forecasting by using ARIMA transfer function model", Proceedings of International Conference on Energy Management and Power Delivery, vol. 1, p.p. 317-322, 1995.
[22] H.T. Yang, C.-M. Huang, and C.-L. Huang, "Identification of ARIMA model for short-term load forecasting: an evolutionary approach", IEEE Transactions on Power Systems, vol. 11, p.p. p.p. 403-408, Issue: 1, Feb. 1996.
[23] M. Peng, N.F. Hubele, and G.G. Karadi, "Advancement in the application of neural networks for short-term load forecasting", IEEE Transactions on Power Systems, vol. 7, p.p. 250-257, Issue: 1, 1992.
[24] A.G., Bakirtzis, V. Petridis, M.C. Kiartzis, and A.H. Maissis, "A neural network short-term load forecasting model for the Greek power system", IEEE Transactions on Power Systems, vol. 11, p.p. 858-863, Issue: 2, 1996.
[25] A.D. Papalexopoulos, S. Hao, and T.-M. Peng, "An implementation of a neural network based load forecasting model for the EMS", IEEE Transactions on Power Systems, vol. 9, p.p. 1956-1962, Issue: 4,1994.
[26] A. Khotanzad, R.A. Rohani, and D.J. Maratukulam, "ANNSTLF - artificial neural network short-term load forecaster - generation three", IEEE Transactions on Neural Networks, vol. 13, p.p. 1413-1422, Issue: 4, 1998.
[27] K.L. Ho, Y.Y. Hsu, F.F. Chen, T.E. Lee, C.C. Liang, T.S. Lai, and K.K. Chen, "Short-term load forecasting of Taiwan Power System using a knowledge based expert system", IEEE Transactions on Power Systems, vol. 5, p.p. 1214-1221, 1990.
[28] S. Rahman, and O. Hazim, "Load forecasting for multiple sites: development of an expert system-based technique", Electric Power System Research, vol. 39, p.p. 161-169, Issue:3, December 1996.
[29] S.J. Kiartzis, A.G. Bakirtzis, J.B. Theocharis, and G. Tsagas, "A fuzzy expert system for peak load forecasting: application to the Greek Power System", Proceedings of the 10th Mediterraean Electrotechnical Conference, vol. 3, p.p. 1097-1100, 2000.
[30] V. Miranda, and C. Monteiro, "Fuzzy interference in spatial load forecasting", Proceedings of IEEE Power Engineering Winter Meeting, vol. 2, p.p. 1063-1068, 2000.
[31] S.E. Skarman, and M. Georgiopoulos, "Short-term electrical load forecasting using a fuzzy ARTMAP neural network", Proceedings of the SPIE, p.p. 181-191, 1998.
[32] V.N. Vapnik, The Nature of Statistical Learnig Theory, New York: Springer Verlag, 1995.
[33] M. Mohandes, "Support vector machines for short-term electrical load forecasting", International Journal of Energy Research, vol. 25, p.p. 335-345, 2002.
[34] B.J. Chen, M.V. Chang, M.V. and C.J. Lin, "Load forecasting using support vector machines: a study on EUNITE Competition 2001", IEEE Transactions on Power Systems, vol. 19, p.p. 1821-1830, Issue: 4, 2004.
[35] Y. Li, and T. Fang, (2003), "Wawelet and support vector machines for short-term electrical load forecasting", Proceedings of International Conference on Wawelet Analysis and its Applications, vol. 1, p.p. 399- 404, 2003.
[36] E.A. Feinberg, and D. Genethliou, "Load forecasting", in Applied Mathematics for Restructured Electric Power Systems: Optimization, Control and Computational Intelligence, J.H. Chow, F.F: Wu and J.J. Momoh (eds), Springer, 2005.
[37] S. Varadan, and E.B. Makram, "Harmonic load identification and determination of load composition using a least squares method", Electric Power System Research, vol. 37, p.p. 203-208, Issue: 3, 1996.
[38] O. Hyde, and P.F. Hodnett, "Modeling the effect of weather in shortterm electricity load forecasting", Mathematical Engineering in Industry, vol. 6, p.p. 155-169, 1997.
[39] R.P. Broadwater, A. Sargent, A. Yarali, H.E. Shaalan, and J. Nazarko, "Estimating substation peaks from research data", IEEE Transactions on Power Systems, vol. 12, p.p. 451-456, Issue: 1, 1997.
[40] A.Z. Al-Garni, Z. Ahmed, Y.N. Al-Nassar, S.M. Zubair, and A. Al- Shehri, "Model for electric energy consumption in eastern Saudi Arabia", Energy Sources, vol. 19, p.p. 325-334, 1997.
[41] H.K. Alfares, and M. Nazeeruddin, "Regression-based methodology for daily peak load forecasting", Proceedings of the 2nd International Conference on Operation and Quantitative Management, Ahmedabad, India, pp.468-471, 3-6 January, 1999.
[42] M. Smith, "Modeling and short-term forecasting of New South Wales electricity system load", Journal of Business & Economic Statistic, vol. 18, p.p. 465-478. 2000.
[43] A. Misiorek, and R. Weron, "Application of external variables to increase accuracy of system load forecast", Proceedings of APE05 Conference, (in Polish), Jurata, 2005.
[44] J.W. Taylor, and R. Buizza, (2003), "Using weather ensemble predictions in electricity demand forecasting", International Journal of Forecasting, vol. p.p. 19, 57-70, 2003.
[45] I. Moghram, and S. Rahman, "Analysis and evaluation of five short-term load forecasting techniques", IEEE Transactions on Power Systems, vol. 4, p.p. 1484-1491, Issue: 4, October 1989.
[46] E.H. Barakat, M.A. Qayyum, M.N. Hamed, and S.A. Al-Rashed, "Short-term peak demand forecasting in fast developing utility with inherent dynamic load characteristic", IEEE Transactions on Power Systems, vol. 5, p.p. 813-824, Issue: 3, 1990.
[47] A.A. El-Keib, X. Ma, and H. Ma, "Advancement of statistical based modeling for short-term load forecasting", Electric Power System Research, vol. 35, p.p. 51-58, Issue: 1, October 1995.
[48] D.G. Infield, and D.C. Hill, "Optimal smoothing for trend removal in short term electricity demand forecasting", IEEE Transactions on Power Systems, vol. 13, p.p. 1115-1120, Issue: 3, 1998.
[49] K. Liu, S. Subbarayan, R.R. Shoults, M.T. Manry C. Kwan, F.L. Lewis, and J. Naccarino, "Comparison of very short-term load forecasting", IEEE Transactions on Power Systems, vol. 11, p.p. 877-882, Issue: 2, 1996.
[50] G.A. Mbamalu, and M.E. El-Hawary, "Load forecasting via suboptimal autoregressive models and iteratively reweighted least squares", IEEE Transactions on Power Systems, vol. 8, p.p. 343-348, Issue: 1, 1993.
[51] A.A. El-Keib, X. Ma, and H. Ma, "Advancement of statistical based modeling for short-term load forecasting", Electric Power System Research, vol. 35, p.p. 51-58, Issue:1 , October 1995.
[52] S.R. Huang, "Short-term load forecasting using threshold autoregressive models", IEE Proceedings: Generation, Transmission, and Distribution, vol. 144, p.p. 477-481, Issue: 5, 1997.
[53] L.J. Soares, and M.C. Medeiros, "Modeling and forecasting short-term electricity load: a two-step methodology", Discussion Paper n┬░. 495, Department of Economics, Pontifical Catholic University of Rio de Janeiro, 2005.
[54] E.H. Barakat, J.M. Al-Qassim, and S.A. Al-Rashed, "New model for peak demand forecasting applied to highly complex load characteristics of a fast developing area", IEE Proceedings C in Generation, Transmission and Distribution, vol. 139, p.p. 136-149, Issue: 2, Mar. 1992.
[55] J.F. Chen, W.M.Wang, and C.M. Huang, C.M., "Analysis of an adaptive time-series autoregressive moving-average (ARMA) model for shortterm load forecasting", Electric Power Systems Research, vol. 34, p.p. 187-196, Issue: 3, September 1995.
[56] L.D. Paarmann, and M.D. Najar-s, "Adaptive on-line forecasting via time series modeling", Electric Power System Research, vol. 32, p.p. 219-225, Issue: 3, March 1995.
[57] J. Nowicka-Zagrajek, and R. Weron, "Modeling electricity loads in California: ARMA models with hyperbolic noise", Signal Processing, vol. 82, p.p. 1903-1915, Issue: 12, December 2002.
[58] S.J. Huang, and K.R. Shih, "Short-term load forecasting via ARMA model identification including non-Gaussian process consideration", IEEE Transactions on Power Systems, vol. 18, p.p. 673-679, Issue: 2, 2003.
[59] Z.S. Elrazaz, and , A.A. Mazi, "Unified weekly peak load forecasting for fast growing power system", IEE Proceedings C - Generation, Transmission and Distribution, vol. 136, p.p. 29-41, Issue: 1, Jan. 1989.
[60] N. Amjadi, "Short-term hourly load forecasting using time-series modeling with peak load estimation capability", IEEE Transactions on Power Systems, vol. 16, p.p. 798-805, Issue: 4, 2001.
[61] G. Juberias, R. Yunta, J. Garcia Morino, and C. Mendivil, "A new ARIMA model for hourly load forecasting", IEEE Transmission and Distribution Conference Proceedings, vol. 1, p.p. 314-319, 1999.
[62] L. Ljung, System Identification - Theory for the User, 2nd edn, Prentice Hall, Upper Saddle River, 1999.
[63] A. Khotanzad, R. Afkhami-Rohani, Tsun-Liang Lu; A. Abaye, M. Davis, D.J. Maratukulam, "ANNSTLF-a neural-network-based electric load forecasting system ", IEEE Transaction on Neural Network, vol. 8, p.p. 835-846, Issue: 4, 1997.
[64] H.S. Hippert, D.W. Bunnand and R.C. Souza, "Large neural networks for electricity load forecasting: are they overfitted?, International Journal of Forecasting, vol. 21, 3, 425-434, Issue: 3, 2005.
[65] K.L. Ho, Y.Y. Hsu, F.F. Chen, T.E. Lee, C.C. Liang, T.S. Lai, and K.K. Chen, "Short-term load forecasting of Taiwan Power System using a knowledge based expert system", IEEE Transactions on Power Systems, vol. 5, p.p. 1214-1221, Issue: 4, 1990.
[66] S. Rahman, and O. Hazim, "Load forecasting for multiple sites: development of an expert system-based technique", Electric Power System Reseach, vol. 39, p.p. 161-169, Issue: 3, December 1996.
[67] K.-H. Kim, J.-K. Park, K.-J. Hwang, and S.-H. Kim, "Implementation of hybrid short-term load forecasting system using artificial neural networks and fuzzy expert systems", IEEE Transactions on Power Systems, vol. 10, p.p. 1534-1539, Issue: 3, 1995.
[68] D. Srinivasan, S.S. Tan. C.S. Chang., and E.K. Chan, "Parallel neural network-fuzzy expert system for short-term load forecasting: system implementation and performance evaluation", IEEE Transactions on Power Systems, vol. 14, p.p. 1100-1106, Issue: 3, 1999.
[69] S.H. Ling, F.H.F. Leung, H.K. Lam, and P.K.S. Tam, "Short-term electric load forecasting based on a neural fuzzy network", IEEE Transactions on Industrial Electronics, vol. 50, p.p. 1305-1316, Issue: 6, 2003.
[70] T. Senjyu, P. Mandal, K. Uezato, and T. Funabashi, "Next day load curve forecasting using hybrid correction methods", IEEE Transactions on Power Systems, vol. 20, p.p. 102-109, Issue: 1, 2005.
[71] K.-B. Song, S.-K. Ha, J.-W. Park, D.-J. Kweon, and K.-H. Kim, "Hybrid load forecasting method with analysis of temperature sensitivities", IEEE Transactions on Power Systems, vol. 21, p.p. 869- 876, Issue: 2, 2006.
[72] V.N. Vapnik, The Nature of Statistical Learning Theory, New York: Springer Verlag, 1995.
[73] Y. Li, and T. Fang, "Application of fuzzy support vector machines in short-term load forecasting", Lecture Notes in Computer Science, 2639, p.p. 363-367, 2003.