i-manager Publications

Development of Improved Recursive Newton Type Algorithm to Estimate Power System Harmonics

Pratap Sekhar Puhan*, Pravat Kumar Ray**

* Department of Electrical and Electronics Engineering, Sreenidhi Institute of Science and Technology, Hyderabad, Telegana, India. ** Department of Electrical Engineering, National Institute of Technology, Rourkela, Odisha, India.

Periodicity:October - December'2019
DOI : https://doi.org/10.26634/jee.13.2.15525

Abstract

Estimation of power system parameters for generation of reference signal is one of the most essential requirements for switching action of the converters. This paper explores the measurement of power system harmonic components with a newly developed Recursive Newton Type algorithm. In the developed algorithm, first the parameters will be updated using Jacobian and Co-variance matrices. Implementation of the co-variance matrix in the proposed algorithm results in fast convergence, minimum computational and settling time, better accuracy of tracking the signals etc. The effect of the developed algorithm is observed in a power system signal through simulations. Effectiveness of the developed algorithm is also examined using Arduino micro-controller. A comparative analysis is made between the Newton Type Algorithm (NTA) and Improved Newton type algorithm to prove the effectiveness of the developed one.

Keywords

Harmonics, Power quality, Estimation, Newton Type Recursive Algorithm, Improved Recursive Newton Type.

How to Cite this Article?

Puhan, P. S., & Ray, P. K. (2019). Development of Improved Recursive Newton Type Algorithm to Estimate Power System Harmonics.i-manager’s Journal on Electrical Engineering(JEE), 13(2), 1-10. https://doi.org/10.26634/jee.13.2.15525

References

[1]. Barros, J., & Pérez, E. (2006). Automatic detection and analysis of voltage events in power systems. IEEE Transactions on Instrumentation and Measurement, 55(5), 1487-1493. https://doi.org/10.1109/TIM.2006.881584

[2]. Begovic, M. M., Djuric, P. M., Dunlap, S. (1993). Frequency tracking in power networks in the presence of harmonics. IEEE Trans Power Delivery. 8(10), 480-486. https://doi.org/10.1109/61.216849

[3]. Chang, G. W., & Chen, C. I. (2010). An Accurate Time- Domain Procedure for Harmonics and Interharmonics Detection. IEEE Transactions on Power Delivery, 3(25), 1787- 1795. https:// doi.org/10.1109%2FTPWRD.2009.2037230

[4]. Jain, S. K., & Singh, S. N. (2012). Exact model order ESPRIT technique for harmonics and interharmonics estimation. IEEE Transactions on Instrumentation and Measurement, 61(7), 1915-1923. https://doi.org/10.1109/ TIM.2012.2182709

[5]. Joorabian, M., Mortazavi, S. S., & Khayyami, A. A. (2009). Harmonic estimation in a power system using a novel hybrid Least Squares-Adaline algorithm. Electric Power Systems Research, 79(1), 107-116. https://doi.org/10. 1016/j.epsr.2008.05.021

[6]. Panda, G., Ray, P. K., & Puhan, P. S. (2014). Harmonic estimation of distorted power system signals employing two hybrid strategies. International Journal of Modelling, Identification and Control, 22(1), 20-32. https://doi.org/10. 1504/IJMIC.2014.063873

[7]. Panda, G., Ray, P. K., Puhan, P. S., & Dash, S. K. (2013). Novel schemes used for estimation of power system harmonics and their elimination in a three-phase distribution system. International Journal of Electrical Power & Energy Systems, 53, 842-856. https://doi.org/10.1016/ j.ijepes.2013.05.037

[8]. Puhan, P. S., Sandeep, S. D., & Sutar, D. (2018). Analysis of Adaptive Linear Neural Network (adaline) in Power System Harmonics Signal. i-manager's Journal on Electrical Engineering, 11(4), 35-42. https://doi.org/10.26634/jee. 11.4.14656

[9]. Ray, P. K., & Subudhi, B. (2012). Ensemble-Kalman-filterbased power system harmonic estimation. IEEE Transactions on Instrumentation and Measurement, 61(12), 3216-3224. https://doi.org/10.1109/TIM.2012.2205515

[10]. Ray, P. K., Puhan, P. S., & Panda, G. (2015). Improved recursive Newton Type Algorithm based power system frequency estimation. International Journal of Electrical Power & Energy Systems, 65, 231-237. https://doi.org/10. 1016/j.ijepes.2014.10.017

[11]. Ray, P. K., Puhan, P. S., & Panda, G. (2016). Real time harmonics estimation of distorted power system signal. International Journal of Electrical Power & Energy Systems, 75, 91-98. https://doi.org/10.1016/j.ijepes.2015.08.017

[12]. Reddy, J. B. V., Dash, P. K., Samantaray, R., & Moharana, A. K. (2009). Fast tracking of power quality disturbance signals using an optimized unscented filter. IEEE Transactions on Instrumentation and Measurement, 58(12), 3943-3952. https://doi.org/10.1109/TIM.2009. 2020835

[13]. Seifossadat, S. G., Razzaz, M., Moghaddasian, M., & Monadi, M. (2007). Harmonic estimation in power systems using adaptive perceptrons based on a genetic algorithm. WSEAS Transactions On Power Systems, 11(2), 239-244.

[14]. Tao, C., Shanxu, D., Ting, R., & Fangrui, L. (2010). A robust parametric method for power harmonic estimation based on M-estimators. Measurement, 43(1), 67-77. https://doi.org/10.1016/j.measurement.2009.06.010

[15]. Tsao, T. P., Wu, R. C., & Ning, C. C. (2001). The optimization of spectral analysis for signal harmonics. IEEE Transactions on Power Delivery, 16(2), 149-153. https://doi.org/10.1109/61.915474

[16]. Yilmaz, A. S., Alkan, A., & Asyali, M. H. (2008). Applications of parametric spectral estimation methods on detection of power system harmonics. Electric Power Systems Research, 78(4), 683-693. https://doi.org/10.1016/ j.epsr.2007.05.011

Development of Improved Recursive Newton Type Algorithm to Estimate Power System Harmonics

Abstract

Keywords

How to Cite this Article?

References

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

Purchase Instant Access

Options for accessing this content:

	North Americas,UK, Middle East,Europe		India	Rest of world
	USD	EUR	INR	USD-ROW
Pdf	35	35	200	20
Online	35	35	200	15
Pdf & Online	35	35	400	25