i-manager Publications

Short-Term Load Forecasting For Jordan's Power System

Kamel N.A. Al-Tallaq*

* Senior Member, IEEE Electrical Engineering Department, Al-Jouf University, Al-Jouf, KSA

Periodicity:April - June'2009
DOI : https://doi.org/10.26634/jee.2.4.224

Abstract

One of the requirements for the operation and planning activities of an electrical utility is the prediction of load for the next hour to several days out, known as Short Term Load Forecasting (STLF). Artificial neural network (ANN) techniques have been applied to various subjects in the electrical power system area including electric load forecasting. This paper presents an application of (ANN) to the weekly load forecast problem of Jordan National Power System (JNPS). The ANN is trained with the load patterns corresponding to the forecasting hours and the forecasted load is obtained. Time Series Regression (TSR) modifies the initial forecasted load. A Neural Network (NN) model for the prediction of the seven-day ahead peak load of Jordan power system is developed. For the purpose, Nonlinear Auto Regressive (AR) modeling, using simple Back-propagation NNs architecture, is used. This model was trained using two weeks data window for the most recent daily peak loads. The model treated the peak load at weekdays and weekends altogether. The results showed that the model has satisfactory results for one hour up to a week prediction of JNPS load. The average absolute percent error for the generated forecasts using this model was 0.5%.

Keywords

Short Term Load Forecasting, Artificial neural network, Jordan National Power System

How to Cite this Article?

Kamel N. A. Al-Tallaq (2009). Short-Term Load Forecasting For Jordan's Power System. i-manager’s Journal on Electrical Engineering, 2(4), Apr-Jun 2009, Print ISSN 0973-8835, E-ISSN 2230-7176, pp. 78-83. https://doi.org/10.26634/jee.2.4.224

References

[1]. I. Badran, H. El-Zayyat, and G. Halasa, " Short-Term and Medium-Term Load Forecasting for Jordan's Power System", American Journal of Applied Sciences, Vol. 5, No. 7, pp.763-768, 2008.

[2]. G. Gross and F. D. Galiana, "Short Term Load Forecasting", Proceeding of the IEEE, Vol.75, No. 12, pp.1558-1572, 1987.

[3]. I. Moghram and S. Rahman,"Analysis and Evaluation of Five Short-Term Load Forecasting Techniques', IEEE Trans. On Power Systems, Vol. 4,No. 4, pp. 1484-1491, 1989.

[4]. S. Vermuri, W. L. Huang, and D. L. Nelson, "On-line Algorithm for Forecasting Hourly Loads of an Electric Utility", IEEE Trans. On Power Apparatus and Systems, PAS- 100, No. 8, pp. 3775-3784, 1981.

[5]. W. Christiaanse, "Short Term Load Forecasting Using Exponential Smoothing', IEEE Trans. PAS, Vol. PAS-90, pp. 900-910, 1971.

[6]. J. Tayoda and M. S. Chen,"Application of State Estimation to Short Term Load Forecasting Parts 1 and 2", IEEE Trans. PAS, Vol. PAS-89, pp. 1678-1688, 1970.

[7]. G. E. Box and G. M. Jenkis, "Time Series Analysis Forecasting and Control", Holden-Day, San Fransisco, USA, 1970.

[8]. Saifur Rahman and Ibrahim Moghram, "An Adaptive Knowledge-Based Technique for Weekly Load Forecasting of the Tenth Power System Computation Conference, 8. Gratz, Australia, 19-24, August, 1990, pp. 979-986.

[9]. S. Rahman and R. Bhanager," An Expert System Based Algorithm for Short Term Load Forecasting", IEEE Trans. On Power Systems, Vol. 3, No. 2, pp. 392-399, 1988.

[10]. K. Jabbour, J. F. V. Riverso, D. Lansbergen and W. Meyer," ALFA: Automatic Load Forecasting Assistant", IEEE Trans. On Power Systems, Vol.3, No.3, pp. 908-914, 1988.

[11]. K. L. Low, Y. Hus, C. Liang, and T. Las,"Short-Term Load Forecasting of Taiwan Power System Using a Knowledge Based Expert System", IEEE Trans. On Power Systems, Vol. 5, No. 4, pp. 1214-1221, November 1990.

[12]. Hiroyaki Mori and Hidenovi Kobayashi, "Optimal Fuzzy Inference for Short Term Load Forecasting", IEEE Trans. On power Systems, Vol. 11, No. 1, pp. 390-399, February 1996.

[13]. P. K. Dash, S. Dash and S. Rahman, "A Fuzzy Adaptive Correction Scheme for Short-Term Load Forecasting Using Fuzzy Layered Neural Network", Proceeding of Ann Ps' 95, pp. 432-437, Yokohama, Japan, April 1993.

[14]. C. N. Lu, H. L. Wu and S. Vemuri, " Neural Network Based Short-Term Load Forecasting", IEEE Trans. On Power Systems, Vol. 8, No.1, pp. 336-442, 1993.

[15]. Piras, B. Buchenel and Y. Jaccard, "Heterogeneous Artificial Neural Network for Short Term Load Forecasting", IEEE Trans. On Power Systems, Vol. 2, No.1, pp. 336-442, 1996.

[16]. Yu Chen et al., "Weather Sensitive Short Term Load Forecasting Using Nonfully Connected Artificial Neural Network", IEEE Trans. On Power Systems, Vol. , No.3, pp. 1098-1105, 1992.

[17]. D. C. Park, M. A. El-Sharkawi and R. J. Marks II, "Electric Load Forecasting Using Artificial Neural Network" , IEEE Trans. On Power Systems, Vol. No. 1, pp. 442-449, 1991.

[18]. Laurene Fausett, "Fundamentals of Neural Networks", Prentice Hall International, Inc. 1994.

[19]. D. E. Rumelhart and J. L. McClelland, "Parallel Distributed Processing: Explorations in the Mictrostructure of Cognition Foundations", Vol. 1, Cambridge MA:MIT Press, 1986.

[20]. Ibrahim S. Moghram, Kamel N. Al-Tallaq, " An Artifical Neural Network Application To Weekly Electrical Peak Load Forecasting", Mu'tah Lil-Buhuth wad-Dirasat, Vol. 14, No. 1, pp.147-163, 1999.

If you have access to this article please login to view the article or kindly login to purchase the article

Single Article

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Online	15	15

ADD TO CART

Options for accessing this content:

If you would like institutional access to this content, please recommend the title to your librarian.
If you already have i-manager's user account: Login above and proceed to purchase the article.
New Users: Please register, then proceed to purchase the article.