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 EPE  Vol.5 No.4 , June 2013
A Methodology for Identification of Weather Sensitive Component of Electrical Load Using Empirical Mode Decomposition Technique
Abstract: The expansion planning and operation of all three sectors, generation, transmission and distribution, of power system essentially require load forecasting. Weather conditions have significant impacts on forecasted load, especially short-term and mid-term. A momentous portion of the electrical energy is consumed, especially in cold or hot countries, to mitigate the impact of weather on the daily life of human society. Usually, weather dependent component of load is identified by fitting appropriate non-linear curve to the scatter plot of weather-load model. This technique some times shows lower correlation with weather variables. This paper proposes a new methodology to identify the weather sensitive component of electrical load using empirical mode decomposition (EMD) technique. The proposed methodology is applied to the daily peak load of Dhaka zone of Bangladesh Power System (BPS) of the year 2012. A detailed numerical process to evaluate the weather sensitive portion of the load is also presented. The proposed methodology is validated through statistical error evaluation process. Finally the salient features of the results are discussed.
Cite this paper: N. Masood and Q. Ahsan, "A Methodology for Identification of Weather Sensitive Component of Electrical Load Using Empirical Mode Decomposition Technique," Energy and Power Engineering, Vol. 5 No. 4, 2013, pp. 293-300. doi: 10.4236/epe.2013.54029.
References

[1]   R. L. Sullivan, “Power System Planning,” Mcgraw-Hill Book Company, New York, 1977.

[2]   H. Chen, C. A. Canizares and A. Singh, “ANN-Based Short Term Load Forecasting in Electricity Markets,” Proceedings of the IEEE Power Engineering Society Transmission and Distribution Conference, Vol. 2, pp. 2011, 411-415.

[3]   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, No. 4, 2003, pp. 1581-1586. doi:10.1109/TPWRS.2003.811172

[4]   J. W. Taylor and R. Buizza, “Neural Network Load Fore casting with Weather Ensemble Predictions,” IEEE Transactions on Power Systems, Vol. 17, No. 3, 2002, pp. 626-632. doi:10.1109/TPWRS.2002.800906

[5]   A. Khotanzad, M. H. Davis, A. Abaye and D. J. Maratu kulam, “An Artificial Neural Network Hourly Temperature Forecaster with Applications in Load Forecasting,” IEEE Transactions on Power Systems, Vol. 11, No. 2, 1996, pp. 870-876. doi:10.1109/59.496168

[6]   S. M. Moghaddas-Tafreshi and M. Farhadi, “A Linear Re gression-Based Study for Temperature Sensitivity Analysis of Iran Electrical Load,” Proceedings of the IEEE International Conference on Industrial Technology, Cheng du, 21-24 April 2008, pp. 1-7. doi:10.1109/SUPERGEN.2009.5347944

[7]   G. Y. Chen and J. T. Shi, “Study on the Methodology of Short-Term Load Forecasting Considering the Accumulation Effect of Temperature,” Proceedings of the International Conference on Sustainable Power Generation and Supply, Nanjing, 6-7 April 2009, pp. 1-4.

[8]   E. Contaxi, C. Delkis, S. Kavatza and C Vournas, “The Effect of Humidity in a Weather-Sensitive Peak Load Forecasting Model,” Proceedings of the IEEE Power Systems Conference and Exposition, Atlanta, 29 October-1 November 2006, pp. 1528-1534.

[9]   E. G. Contaxi and S. Kavatza, “Application of a Weather Sensitive Peak Load Forecasting Model to the Hellenic System,” Proceedings of the IEEE Mediterranean, Vol. 3, 2004, pp. 819-822.

[10]   N. E. Huang, Z. Shen, S. R. Long, M. C. Wu, H. Shih, Q. Zheng, N. C. Yen, C. C. Tung and H. H. Liu, “The Empirical Mode Decomposition and the Hilbert Spectrum for Nonlinear and Non-Stationary Time Series Analysis,” Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 454, No. 1971, 1998, pp. 903-995.

[11]   K. I. Molla, K. Hirose and N. Minematsu, “Robust De termination of Periodic Correlation of Speech Signals Using Empirical Mode Decomposition and Higher-Order Spectra,” Proceedings of the Asia-Pacific Conference on Communications, Tokyo, 14-16 October 2008, pp. 1-5.

[12]   K. Khaldi, M. T.-H. Alouane and A.-O. Boudraa, “Speech Denoising by Adaptive Weighted Average Filtering in the EMD Framework,” Proceedings of the International Conference on Signals, Circuits and Systems, pp 1-5.

[13]   N. Chatlani and J. J. Soraghan, “Speech Enhancement using Adaptive Empirical Mode Decomposition,” Proceedings of the IEEE International Conference on Digital Signal Processing, Monastir, 7-9 November 2008, pp. 1-6.

[14]   M. Kiamini, S. Alirezaee, B. Perseh and M. Ahmadi, “Elimination of Ocular Artifacts from EEG Signals Using the Wavelet Transform and Empirical Mode Decomposition,” Proceedings of the International Conference on Electrical Engineering/Electronics, Computer, Telecommunications and Information, Pattaya, 6-9 May 2009, pp. 1094-1097.

[15]   Z. D. Zhao and C. Ma, “A Novel Cancellation Method of Power Line Interference in ECG Signal Based on EMD and Adaptive Filter,” Proceedings of the IEEE International Conference on Communication Technology, Hang zhou, 10-12 November 2008, pp. 517-520.

[16]   X. J. Guo, X. P. Wu and D. X. Zhang, “Motor Imagery EEG Detection by Empirical Mode Decomposition,” Proceedings of the IEEE International Joint Conference on Computational Intelligence and Neural Networks, Hong Kong, 1-8 June 2008, pp. 2619-2622.

[17]   P. F. Diez, V. Mut, E. Laciar, A. Torres and E. Avila, “Application of the Empirical Mode Decomposition to the Extraction of Features from EEG Signals for Mental Task Classification,” Proceedings of the IEEE International Conference on Engineering in Medicine and Bio logy Society, Vol. 2009, 2009, pp. 2579-2582.

[18]   T. Q. Zhu, L. Y. Huang and X. Z. Tian, “Epileptic Seizure Prediction by Using Empirical Mode Decomposition and Complexity Analysis of Single-Channel Scalp Electroencephalogram,” Proceedings of the IEEE International Conference on Biomedical Engineering and Informatics, Tianjin, 17-19 October 2009, pp. 1-4.

[19]   http://www.dairynz.co.nz

 
 
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