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Detection and analysis of power quality disturbances under faulty conditions in electrical
1.
INTERNATIONAL JOURNAL OF
ELECTRICAL ENGINEERING International Journal of Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME & TECHNOLOGY (IJEET) ISSN 0976 – 6545(Print) ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), pp. 25-36 IJEET © IAEME: www.iaeme.com/ijeet.asp Journal Impact Factor (2013): 5.5028 (Calculated by GISI) ©IAEME www.jifactor.com DETECTION AND ANALYSIS OF POWER QUALITY DISTURBANCES UNDER FAULTY CONDITIONS IN ELECTRICAL POWER SYSTEM Devendra Mittal1, Om Prakash Mahela2, Rohit Jain3 1 Assistant Professor, Dept. of Electrical Engg., Jagannath University Jaipur, India 2 Graduate Student Member IEEE & Junior Engineer-I, RRVPNL, Jaipur, India 3 Professor, Department of Physics, JNIT, Jaipur, India ABSTRACT The electrical power of good quality is essential for proper operation of many electronic equipment, power electronics based loads and microprocessor based controlled loads. Malfunction of equipment may lead to loss of production or disruption of critical services resulting in huge financial and other losses. The power quality disturbances decrease the efficiency of power system equipments such as generators. Therefore the issue of power quality is very important to both the consumers and the utility of electric power. There are many facets of power quality disturbances and each has its own source and mitigation techniques. The first step towards any solution for a disturbance is to recognize the presence of a particular type of disturbance and locate its source. This paper deals with detection, analysis and travel of power quality disturbances under faulty conditions in electrical power system. A four bus system having two load and two generator buses is modeled in MATLAB/Simulink environment. A fault is created near the load bus and power quality disturbances are detected near the generator bus. Keywords: power system, power quality, power system faults, power quality disturbance. 25
2.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 1. INTRODUCTION An electrical power system is expected to deliver undistorted sinusoidal rated voltage and current continuously at rated frequency to the end users [1]. Poor quality of electric power is normally caused by power line disturbances, such as impulses, notches, glitches, momentary interruption wave faults, voltage sag, swell, harmonic distortion and flicker resulting in misoperation or failure of end user equipment [2]. The meaning of power quality is different in views of utility, equipment manufacturers, and customers. Utilities treat PQ from the system reliability point of view. Equipment manufacturers, on other hand, consider PQ as being that level of power supply allowing for proper operation of their equipment. Customer considers good PQ that ensures the continuous running of processes. A number of papers have been published during the last several years on detections and classification of power quality disturbances. The approach of neural networks has been used by [3] for the purpose of PQ disturbance detection. The use of continuous wavelet transform (CWT) to analyse non-stationary harmonic distortion has been proposed by [4]. Studies on PQ assessment by using a dynamic orthogonal wavelet were carried out by [5]. An improved Hilbert-Huang method for analysis of time varying waveforms in power quality has been proposed by [6]. The discrete wavelet transform and S-transform based neural classifier scheme for time series data mining of power quality events occurring due to power signal disturbances has been proposed by [7]. Most of papers published on power quality are concerned with the customer related issues. This paper aims to detect power quality disturbances in the faulty conditions of the power system. The four bus system with two load and two generator buses is simulated in MATLAB/Simulink environment. The Power Quality disturbances are detected at generator bus in the healthy condition and with LG fault, LL fault, LLG fault, LLL fault and LLLG fault on the load bus. The results obtained after simulation demonstrate the nature of different disturbances during faulty conditions in the power system. 2. POWER QUALITY DISTURBANCES IN POWER SYSTEM The term power quality (PQ) is generally applied to a wide variety of electromagnetic phenomena occurring within a power system network. Power quality is predominately a customer issue [8]. The power quality problem can be defined as any problem manifested in voltage, current or frequency deviations that result in failure or mal-operation of customer equipment [9]. It covers several types of problems of electricity supply and power system disturbances. According to IEEE standard 1159-1995 [10], the PQ disturbances include wide range of PQ phenomena namely transient (impulsive and oscillatory), short duration variations (interruption, sag and swell), power frequency variations, long duration variations (harmonics, notch, flicker etc.) with time scale ranges from tens of nanoseconds to steady state. Inigo Monedero et al. [11] presented a classification of PQ disturbances, which is given in Table.I, based on the UNE standard in Spain which defines the ideal signal as a single- phase sinusoidal voltage signal of 230 Vrms and 50 Hz. A number of causes of power quality transients can be identified: lightning strokes, planned switching actions in the distribution or transmission system, self-clearing faults or faults cleared by current limiting fuses, and the switching of end-user equipment. Transient phenomena are extremely critical since they can cause over voltages leading to insulation breakdown or flashover. These failures might trip any protection device initiating a short interruption to the supplied power. Excess current 26
3.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME produced by transients may lead to complete damage to system equipment during the transient period. Moreover, if such disturbances are not mitigated, they can lead to failures or malfunctions of various sensitive loads in power systems and may be very costly [12]. TABLE I TYPES OF DISTURBANCES Range Type of Disturbance subtype Time disturbance Max. Min. Value Value Slight deviation 49.5 Hz. 50.5 Hz. Frequency 10 s Severe deviation 47.0 Hz. 52.0 Hz. Average voltage 10 min 0.85 Un 1.1 Un Flicker - - 7% Short 10ms-1s Sag Long 1s-1min 0.1 U 0.9 U Long-time disturbance >1min Voltage Short <3min Under Voltage 0.99 U Long >3min Temporary Short 10ms-1s Swel Temporary Long 1s-1min 1.5 KV 1.1 U l Temporary Long-time >1min Over-voltage <10 ms 6 KV Harmonics and Harmonics - THD>8% other information Included in other signals Information signals - disturbances A lot of research works have been carried out in the classification of power quality events and recognition and identification of power quality disturbances. A wavelet based fuzzy reasoning approach to power quality disturbance recognition and identification has been presented in [13]. Wavelet transform can be used in conjunction with Kalman filter for online real time detection and classification of voltage events in power system [14]. Dash P.K. et al. [15] used S-transform for detecting, localizing, and classifying PQ problems. Haibo He et al. [16] proposed an energy difference of multi-resolution analysis (EDMRA) method for power quality disturbances analysis. At each wavelet decomposition level, the squared value of the detail information is calculated as their energy to construct the feature vector for analysis. Following the criteria proposed in this paper, different kinds of power quality disturbances can be detected, localized, and classified effectively. 27
4.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 3. THE PROPOSED POWER SYSTEM MODEL For detections of power quality disturbances during faulty conditions in the power system, the one line diagram of experimental set up consisting of four buses is shown in Fig. 1. The buses 1 & 2 are taken as generator buses and buses 3 & 4 are taken as load buses. The line length of all the four π sections are taken as 100 Km. For simplicity the voltage levels at all points of the system are taken as 33 KV. The fault is located at bus no. 4 in all faulty conditions considered in the study. All the measurement of the voltage signals are taken on bus no. 1 at generating station. Fig. 1 Proposed model of Power System for detection of PQ disturbances in faulty conditions 4. DETECTION AND ANALYSIS OF PQ DISTURBANCES IN FAULTY CONDITIONS In the power system, faults are abnormal events which are not part of normal operation and unwanted by the network operator. After fault occurs in the power system, a non-linear signal of transient travelling wave is generated and runs along faulted transmission line to both ends of the line. Those travelling waves contain information about fault nature. The fault initial travelling wave has a wide frequency spectrum from DC component to high frequencies. When such fault travelling wave arrives at the substation bus bar, it will change incisively, i.e. travelling wave head will present the sudden change in the time-frequency diagram. In that way, travelling wave arrival to the measuring point (usually the busbar voltage transformers) is exactly a moment of sudden change recorded on measuring substation [17]. MATLAB is a user friendly software and used in many field for research. For experimental detections of power quality disturbances during faulty conditions in the proposed model of power system, the MATLAB simulation is performed in healthy conditions as well as in faulty conditions. 4.1 Power System in Healthy Conditions The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment in healthy condition. The Voltage signal of phase-A and Fourier Signals on phase-A are shown in Fig. 2 and Fig. 3 respectively. In healthy conditions the signals on all 28
5.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME the three phases are similar. In healthy conditions the voltage in all the three phases are identical. The symmetrical wave of 50Hz frequency is obtained. The fourier analysis of the voltage signals also shows the symmetry in healthy conditions. Fig. 2 Voltage signal on Phase-A in healthy condition at bus-1 Fig. 3 Fourier analysis of signal on Phase-A in healthy condition at bus-1 4.2 LG Fault on Power System The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment with line to ground fault at bus no. 4 on phase-A. The voltage signal of phase-A, voltage signal of phase-B and Fourier Signals on Phase-A at bus no. 1 are shown in Fig. 4, Fig. 5 and Fig. 6 respectively. The multiple voltage spikes of magnitude of the order 106 are obtained on the faulty phase and that of 105 are obtained on the healthy phases. The presence of multiple voltage spikes is also validated by the fourier analysis of signals. 29
6.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME Fig. 4 Voltage signal on Phase-A at bus-1 with LG fault on phase-A at bus-4 Fig. 5 Voltage signal on Phase-B at bus-1 with LG fault on phase-A at bus-4 Fig. 6 Fourier analysis of signal on Phase-A at bus-1 with LG fault on phase-A at bus-4 30
7.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 4.3 LL Fault on Power System The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment with double line (LL) fault at bus no. 4 on phases A & B. The voltage signal of phase-A, voltage signal of phase-C and Fourier Signals on phase-A at bus no. 1 are shown in Fig. 7, Fig. 8 and Fig. 9 respectively. The multiple voltage spikes of the magnitude of order 107 are detected on the faulty phases and voltage of power frequency is detected on the healthy phases. The presence of multiple voltage spikes of high magnitude is confirmed by the fourier analysis of voltage signal. Fig. 7 Voltage signal on Phase-A at bus-1 with LL fault on phases A & B at bus-4 Fig. 8 Voltage signal on Phase-C at bus-1 with LL fault on phases A & B at bus-4 31
8.
International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME Fig. 9 Fourier analysis of signal on Phase-A at bus-1 with LL fault on phases-A&B at bus-4 4.4 LLG Fault on Power System The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment with double line to ground (LLG) fault at bus no. 4 on phases A & B. The voltage signal of phase-A, voltage signal of phase-C and Fourier Signals on Phase-A at bus no. 1 are shown in Fig. 10, Fig. 11 and Fig. 12 respectively. The multiple voltage spikes of the magnitude of order 108 are detected on the faulty phases and that of order of 107 is detected on the healthy phase. The presence of multiple voltage spikes of high magnitude is confirmed by the fourier analysis of voltage signal. Fig. 10 Voltage signal on Phase-A at bus-1 with LLG fault on phases A & B at bus-4 32
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International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME Fig. 11 Voltage signal on Phase-C at bus-1 with LLG fault on phases A & B at bus-4 Fig. 12 Fourier analysis of signal on Phase-A at bus-1 with LLG fault on phases-A&B at bus-4 4.5 LLL fault on Power System The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment with three phase (LLL) fault at bus no. 4. The voltage signal of phase-A and Fourier Signals on phase-A at bus no. 1 are shown in Fig. 13, and Fig. 14 respectively. The voltage swell is detected on all the phase voltages of the system. The presence of voltage swell in the system voltage because of LLL fault on the system is confirmed by the fourier analysis of voltage. Fig. 13 Voltage signal on Phase-A at bus-1 with LLL fault bus-4 33
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International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME Fig. 14 Fourier analysis of signal on Phase-A at bus-1 with LLL fault at bus-4 4.6 LLLG Fault on Power System The power system model shown in Fig. 1 is simulated in MATLAB/Simulink environment with three phase fault including ground (LLLG) fault at bus no. 4. The voltage signal of phase-A and Fourier Signals on phase-A at bus no. 1 are shown in Fig. 15, and Fig. 16 respectively. The multiple voltage spikes of high frequency persist for long time in case of LLLG fault on the system. The magnitude of voltage spike is detected of the order of 106. The presence of high frequency voltage swell is confirmed by the fourier analysis of voltage signal. Fig. 15 Voltage signal on Phase-A at bus-1 with LLLG fault bus-4 Fig. 16 Fourier analysis of signal on Phase-A at bus-1 with LLLG fault at bus-4 34
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International Journal of
Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME 5. CONCLUSION An efficient but simple technique has been developed to detect the power quality disturbances during faulty conditions in the electrical power system. The proposed model of the four bus system is simulated in the MATLAB/Simulink environment. The results show the relative severity of impacts of power quality disturbances during different types of faults on the power system. The voltage spikes are detected in all types of unsymmetrical faults. The LL and LLG faults are more severe and develop voltage spikes of high magnitude and frequency as compared to the LG fault. In the symmetrical fault (LLL) condition voltage swell of high frequency is observed and voltage swells are converted to the voltage spikes when ground is involved in LLLG fault conditions. REFERENCES [1] D.Saxena, K.S. Verma, and S.N. Singh, “Power quality event classification: an overview and key issues,” International Journal of Engineering, Science and Technology, Vol. 2, No. 3, 2010, pp. 186-199. [2] Subhamita Roy, and Sudipta Nath, “Classification of power quality disturbances using features of signals,” International Journal of Scientific Publications, Vol. 2, Issue 11, November 2012, pp.01-09. [3] N. Kandil, V.K.Sood, K.Khorasani, and R.V. Patel, “Fault identification in an AC-DC transmission system using neural networks,” IEEE transactions on Power System, Vol. 7, No. 2, May 1992, pp. 812-819. [4] P.F. Ribeiro, “Wavelet transform: an advanced tool for analyzing non-stationary harmonics distortions in power systems,” Proceedings of the IEEE International Conference on Harmonics in Power Systems, Bologna, Italy, September 1994. [5] S. Santoso, et al., “Power quality assessment via wavelet transform analysis,” IEEE Transactions on Power Delivery, Vol. 11, No. 2, April 1996, pp. 924-930. [6] Nilanjan Senroy, Siddharath Suryanarayanan, and Paulo F. Ribeiro, “An improved hilbert- huang method for analysis of time varying waveforms in power quality,” IEEE transactions on Power Systems, Vol. 22, No. 4, November 2007, pp. 1843-1850. [7] Lalit Kumar Behera, Maya nayak, and Sareeta Mohanty, “Discrete wavelet transforms and S- transform based time series data mining using multilayer perception neural network,” International Journal of Engineering and Technology, Vol. 3, No. 11, November 2011, pp. 8039-8046. [8] Devendra Mittal, Om Prakash Mahela, and Rohit Jain, “Classification of power quality disturbances in electric power system: A review,” IOSR Journal of Electrical and Electronics Engineering, Vol. 3, Issue. 5, Nov.-Dec. 2012, pp. 06-14. [9] R. Dugan, M. McGranaghan, and H. Wane Beaty, Electrical Power Systems Quality, McGraw- Hill, New York, 1996. [10] IEEE Standards Board, IEEE Std. 1159-1995, “IEEE Recommended Practice for Monitoring Electric Power Quality,” New York: IEEE, Inc. June, 1995. [11] Inigo Monedero, Carlos Leon, Jorge Ropero, Antonio Garcia, Jose Manuel Elena, and Juan C. Montano, “Classification of electrical disturbances in real time using neural networks,” IEEE Transactions on Power Delivery, [Online] DOI: 10.1109/TPWRD.2007.899522,2007, pp. 01- 09. [12] R. Swarna Latha, Ch. Sai Babu, and K. Durga Syam Prasad, “Detection & analysis of power quality disturbances using wavelet transforms and SVM,” International Research Journal of Signal Processing, Vol. 02, Issue 02, Aug.-Dec. 2011, pp. 58-69. [13] Zhu T., Tso S.K., and Lo K.L., “Wavelet-based fuzzy reasoning approach to power quality disturbance recognition,” IEEE Transactions on Power Delivery, Vol. 19, No. 4, 2004, pp. 1928-1935. 35
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Electrical Engineering and Technology (IJEET), ISSN 0976 – 6545(Print), ISSN 0976 – 6553(Online) Volume 4, Issue 2, March – April (2013), © IAEME [14] Perez E., Barros J., “A proposal for on-line detection and classification of voltage events in power systems,” IEEE Transactions on Power Delivery, Vol. 19, No. 4, 2008, pp. 2132-2138. [15] Dash P.K., Panigrahi B.K., and Panda G., “Power quality analysis using S-transform,” IEEE Transactions on Power Delivery, Vol. 18, No. 2, 2003, pp. 406-411. [16] Haibo He, Xiaoping Shen, and Janusz A. Starzyk, “Power quality disturbances analysis based on EDMRA method,” Elsevier Journal of Electrical Power and Energy Systems, Vol. 31, 2009, pp. 258-268. [17] Alen Bernadic, and Zbigniew Leonowicz. “Power line fault location using the complex space- phasor and Hilbert-huang transform,” Przeglad Elektrotechniczny (Electrical Review), R.87 NR 5/2011, pp. 204-207. [18] V. Niranjan and Ch. Das prakash, “Implementation of Wavelets with Multilayer and Modular Neural Network for the Compensation of Power Quality Disturbances” International Journal of Electrical Engineering & Technology (IJEET), Volume 3, Issue 1, 2012, pp. 79 - 87, ISSN Print : 0976-6545, ISSN Online: 0976-6553 Published by IAEME. BIOGRAPHIES Devendra Mittal was born in Bhusawar in the Rajasthan state of India, on March 17, 1980. He studied at IET, Alwar, and received the electrical engineering degree from Rajasthan University, Jaipur, in 2003. He received M.Tech.(Power system) from MNIT, Jaipur, in 2007. He is currently pursuing Phd from Jagannath University, Jaipur. From 2003 to 2008, he was Lecturer with Shankara Institute of Technology, Jaipur. From 2008 to 2009, he was Lecturer with UDML Engineering College. Since 2009, he has been Assistant Professor with Jagannath University, Jaipur, India. His special fields of interest are, Power Electronics and Power System. Om Prakash Mahela was born in Sabalpura (Kuchaman City) in the Rajasthan state of India, on April 11, 1977. He studied at Govt. College of Engineering and Technology (CTAE), Udaipur, and received the electrical engineering degree from Maharana Pratap University of Agriculture and Technology (MPUAT), Udaipur, India in 2002. He is currently pursuing M.Tech. (Power System) from Jagannath University, Jaipur, India. From 2002 to 2004, he was Assistant Professor with the RIET, Jaipur. Since 2004, he has been Junior Engineer-I with the Rajasthan Rajya Vidhyut Prasaran Nigam Ltd., Jaipur, India. His special fields of interest are Transmission and Distribution (T&D) grid operations, Power Electronics in Power System, Power Quality and Load Forecasting. He is an author of 18 International Journals and Conference papers. He is a Graduate Student Member of IEEE. He is member of IEEE Communications Society. He is Member of IEEE Power & Energy Society. Mr. Mahela is recipient of University Rank certificate from MPUAT, Udaipur, India, in 2002. Dr. Rohit Kumar Jain is Professor, Department of Physics, JaganNath Gupta Institute of Engineering & Technology, Jaipur. He has an experience of teaching engineering physics for more than 15 years. He received his Ph.D. degree from University of Rajasthan Jaipur in the field of metallic glasses. He has more than 15 research publications in National and International journals. He has published two books, Hand Book of Engineering Practical Physics-I & II from Vardhan Publisher & Distributor, Jaipur and Engineering Physics, Vol. I & II from Vigyan & Takniki Prakashan, Jaipur. 36
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