Load Identification Using Harmonic Based on Probabilistic Neural Network
Abstract
Due to increase power quality which are caused by harmonic distortion it could be affected malfunction electrical equipment. Therefore, identification of harmonic loads become important attention in the power system. According to those problems, this paper proposes a Load Identification using harmonic based on probabilistic neural network (PNN). Harmonic is obtained by experiment using prototype, which it consists of microcontroller and current sensor. Fast Fourier Transform (FFT) method to analyze of current waveform on loads become harmonic load data. PNN is used to identify the type of load. To load identification, PNN is trained to get the new weight. Testing is conducted To evaluate of the accuracy of the PNN from combination of four loads. The results demonstrate that this method has high accuracy to determine type of loads based on harmonic loadDownloads
References
IEEE std. 519-1992 IEEE Recommended Practices and Requirement for Harmonic Control in Electrical Power Systems.
G.T. Heydt, Identification of Hharmonic sources by a state estimation technieque, IEEE Trans. Power Del. Vol. 4 no. 1, pp. 569-576, jan. 1989.
H. Ma and A. A. Girgis, Identification and tracking of harmonic sources in a power system using a Kalman FIlter, IEEE Trans. Power Del., vol. 11, no. 3, pp. 1659-1665, jul. 1996.
F. Sultanem, Using appliance signatures for monitoring residential loads at meter panel level, IEEE Trans. Power Del., vol. 6, no. 4, pp. 1380–1385, Oct. 1991.
G.W. Hart, Nonintrusive appliance load monitoring, Proc. IEEE, vol. 80, no. 12, pp. 1870–1891, Dec. 1992.
D. C. Robertson, O. I. Camps, J. S. Mayer, and W. B. Gish, Sr., Wavelets and electromagnetic power system transients, IEEE Trans. Power Del., vol. 11, no. 2, pp. 1050–1056, Apr. 1996.
A. I. Cole and A. Albicki, Data extraction for effective non-intrusive identification of residential power loads, in Proc. IEEE Instrum. Meas.Technol. Conf., 1998, pp. 812–815.
I. Cole and A. Albicki, Algorithm for non-intrusive identification of residential appliances, in Proc. IEEE Int. Symp. Circuits Syst., 1998, pp. 338–341.
Anggriawan, D.O., Satriawan, A.L., Sudiharto, I., Wahjono, E., Prasetyono, E., Tjahjono, A., “Levenberg Marquardt Backpropagation Neural Network for Harmonic Detectionâ€, International Electronics Symposium on Engineering Technology and Application (IES-ETA), 2018
Sudiharto, I., Anggriawan, D.O., Tjahjono, A., Harmonic Load Identification Based on Fast Fourier Transform and Levenberg Marquardt Backpropagation, Journal of Theoretical and Applied Information Technology, vol. 95, Iss. 5, pp. 1080, 2017
Mubarok, A.F., Octavira, T., Sudiharto, I., Wahjono, E., Anggriawan, D.O., “Identification of Harmonic Loads Using Fast Fourier Transform and Radial Basis Function Neural Networkâ€, International Electronics Symposium on Engineering Technology and Application (IES-ETA), 2017
M. T. Musav1, W. Ahmed, K. H. Chan, K. B. Faris, T And D. M. Hummels, On the Training of Radial Basis Function Classifiers, Pergamon Press Ltd. Neural Networks vol. 5, pp. 595-603. 1992.
Young-Sup Hwang and Sung-Yang Bang, An Efficient Method to Construct a Radial Basis Function Neural Network Classifier, Elsevier Science Ltd, Neural Networks. vol. 10, no. 8, 1997.
J.A Leonard, M.A Kramer, Radial basis function networks for classifying process faults, IEEE Control Systems, Vol. 11, No. 3, April. 1991.
Wu, Sthephen Gang. 2007. A leaf recognition algorithm for plant clasification using probabilistic neural network. IEEE ISSPIT 2007 on computer science and electrical engineering involve artificial intelligence and Neurology.
F. Zhang, Z. Geng, W. Yuan, The Algorithm of interpolating Windowed FFT for harmonic Analysis of electric Power System, IEEE Trans. Power Del., Vol. 16, No. 2, Apr. 2001.
H.Qian, R. Zhao, T. Chen, Interhamonics Analysis Based on Interpolating Windowed FFT Algorithm IEEE Trans. Power Del, Vol. 22, no. 2, Apr. 2007.
Copyright (c) 2019 EMITTER International Journal of Engineering Technology
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
The copyright to this article is transferred to Politeknik Elektronika Negeri Surabaya(PENS) if and when the article is accepted for publication. The undersigned hereby transfers any and all rights in and to the paper including without limitation all copyrights to PENS. The undersigned hereby represents and warrants that the paper is original and that he/she is the author of the paper, except for material that is clearly identified as to its original source, with permission notices from the copyright owners where required. The undersigned represents that he/she has the power and authority to make and execute this assignment. The copyright transfer form can be downloaded here .
The corresponding author signs for and accepts responsibility for releasing this material on behalf of any and all co-authors. This agreement is to be signed by at least one of the authors who have obtained the assent of the co-author(s) where applicable. After submission of this agreement signed by the corresponding author, changes of authorship or in the order of the authors listed will not be accepted.
Retained Rights/Terms and Conditions
- Authors retain all proprietary rights in any process, procedure, or article of manufacture described in the Work.
- Authors may reproduce or authorize others to reproduce the work or derivative works for the author’s personal use or company use, provided that the source and the copyright notice of Politeknik Elektronika Negeri Surabaya (PENS) publisher are indicated.
- Authors are allowed to use and reuse their articles under the same CC-BY-NC-SA license as third parties.
- Third-parties are allowed to share and adapt the publication work for all non-commercial purposes and if they remix, transform, or build upon the material, they must distribute under the same license as the original.
Plagiarism Check
To avoid plagiarism activities, the manuscript will be checked twice by the Editorial Board of the EMITTER International Journal of Engineering Technology (EMITTER Journal) using iThenticate Plagiarism Checker and the CrossCheck plagiarism screening service. The similarity score of a manuscript has should be less than 25%. The manuscript that plagiarizes another author’s work or author's own will be rejected by EMITTER Journal.
Authors are expected to comply with EMITTER Journal's plagiarism rules by downloading and signing the plagiarism declaration form here and resubmitting the form, along with the copyright transfer form via online submission.