SVC Compensated Multi Terminal Transmission System Digital Protection Scheme using Wavelet Transform Approach

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1 SVC Compensated Multi Terminal Transmission System Digital Protection Scheme using Wavelet Transform Approach J.Uday Bhaskar 1, S.S Tulasiram 2, G.Ravi Kumar 3 JNTUK 1, JNTUH 2, JNTUK 3 udayadisar@gmail.com Abstract AC exact fault classification and faulty terminal identification in SVC compensated multi terminal transmission system is proposed. The multi terminal transmission systems are usually compensated with FACTS devices like static var compensators which are required during faults to improve power transfer capability and voltage regulation by rapidly supplying the dynamic vars required during faults for voltage support. This paper presents the simulation results of the application of distance relays for the protection of multi terminal transmission system compensated with SVC. The fault indices of all the phases for all the faults at each terminal are obtained through MATLAB simulation using wavelet transform approach with Bior1.5 as mother wavelet. The fault indices were utilized to detect and classify the faults and also to identify the faulty terminal with variations in fault impedance and fault inception angle which are independent of each other. The proposed protection scheme is found to be fast, reliable for detection of various types of faults at all terminals with variations in fault location and fault inception angle. Index Terms Multi terminal transmission system, Wavelet transform, Fault indices, SVC, Threshold value, Fault inception angle I. INTRODUCTION The transient stability of a transmission system can be improved by incorporating FACTS devices like SVC. The static var compensator is mainly used for voltage regulation in transmission and distribution system and can rapidly supply dynamic vars required during faults for voltage support. When reactive power injected or absorbed by SVC, it influences the apparent impedance in over reaching or under reaching of distance relays. The increases in the capital expenditure and obtaining the right-of-way have led to the development of multi terminal transmission system where more than two terminals are interconnected to the system. Protection of such interconnected systems is difficult as compared with two-terminal systems. These terminal lines will have the problems in feed of the currents from the other terminals or an out feed to the terminals generated by the intermediate, changes in the section lengths and source impedances and superimposing of currents which requires the system to be protected under fault conditions. The application of FACTS devices in power systems emphasizes the capability of controlling network conditions and improving voltage stability along with the control of transmission voltage. SVC is a FACTS device which is connected in shunt with the transmission system which gives maximum benefit in terms of stabilized voltage support and maximum power transfer capability. Power transfer in most multi terminal transmission systems is constrained by voltage and power stability which will limit the utilization of transmission networks. M.Kowsalya et al emphasized the optimal positioning of svc along the transmission line [1],where it was located at the middle of the transmission system for enhanced power transfer capability. P.K.Sharma et al have done the work related with the location of the device in series compensated line[2]. P.K.Dash et al have done research work on the performance of distance relays for transmission system with different facts devices [3]. Weichen et al have done research related with wavelet based high speed directional transmission line protection [4]. T.S.Sidhu et al obtained the performance of distance relays on shunt facts compensated transmission lines[5].f.a.albasri et al emphasized the impact of shunt facts devices on distance protection of transmission lines[6],where the impact of svc on the performance of transmission lines and the application it is used for and also the location in the transmission system were given and observed whether the existing transmission distance protection relays would perform well with the installation of shunt facts controllers and results shown that the mid-point shunt facts compensation can effect the distance relays with regard to impedance measurement, phase selection and result 2385

2 in under and over reaching of relays in the presence of SVC.Transient current and voltage waveforms were used for fault detection and faulty phase selection[7]. Rekha et al presented the reactive power control of transmission line with firing angle control of SVC[8]. S.A.Hosseini et al presented new method for identifying transmission line faults with high impedance[9].fengliang et al applied wavelet transform and emphasized the performance of digital filters for effective operation of the relays for distance protection[10]. Ravikumar et al proposed the double transmission line protection in the presence of svc with wavelet approach[11]. Bo,Z.Q proposed a protection schemes for multi-terminal transmission circuits such as unit and non-unit schemes. The unit schemes requires more extensive communication channels between the line ends[12]. Bhalija,B et al proposed a distance relaying scheme to find high resistance faults on transmission lines[13]. Brahma and Girgis proposed a fault location scheme by using synchronization of transmission line voltage measurements at all terminals[14].lyonette,d.r.m et al proposed a different directional techniques for multi-terminal transmission lines, which compare the polarity of fault generated transient current signals[15]. Bhalija B. et al proposed a differential protection scheme for tapped transmission lines where outfeed current in case of fault conditions [16].Al-Fakhri proposed incremental current based protection scheme for multi-terminal lines [17]. A.I.Megahed, et al proposed wavelet based fault location in two and three terminal lines[18]. There must be advanced methods have to be developed for four terminal transmission line protection. In this work, multi-resolution analysis of wavelets is used for detection and classification of faults and faulty terminal identification on four terminal transmission system. Detail D1 coefficients of current signals at all the four ends are used to detect and classify the faults. The current samples are analyzed taking into consideration that sum of the current coefficients at all the four terminals. II. WAVELET ANALYSIS For analysis of transient currents and voltages, Wavelet Transform (WT) is an effective tool. Unlike Discrete Fourier Transform, Wavelet transform analyses the signal in both frequency and time domains, which uses short and long windows for high and low frequencies respectively. This helps to analyze the signal in both the domains effectively. A set of basis functions called wavelets, which are obtained mother wavelet to decompose the signal in different frequency bands called approximates and details. The amplitude and incidence of each frequency band can be found precisely. Wavelet Transform (WT) is defined as a sequence of functions {h (n)} (low pass filter) and {g (n)} (high pass filter). ⱷ (t), Ψ (t) can be defined by the following equations. t 2 hn 2t n, t 2 gn 2t n (1) Where g (n) = (-1) n h (1-n). This theory gives information related to the frequency and time domain composition of a waveform, thus it is more appropriate than the Fourier methods for non recurring, wide-band signals associated with electromagnetic transients. When compared to the traditional Fourier analysis, Wavelet Transforms provide a new tool for signal processing that averages frequency features both in time and frequency that allow the decomposition of a signal into different levels of resolution which gives a much better signal characterization and more discrimination. The power system transients can be analyzed with Wavelet multi resolution analysis. The feature extraction property of Wavelets Transforms is exploited in protection of transmission lines for detection and classification of the faults. The different types of wavelets include Haar, Daubachies, Symlet, Bior etc. and the selection of mother wavelet is based on the type of application and system configuration; since Bior-1.5 has been found to be effective and chosen as mother wavelet. III. PROPOSED SYSTEM OF STUDY Figure 1 Single line diagram of the proposed four terminal Transmission system. Figure I shows the single line diagram of the multi terminal transmission system considered along with the various blocks of the proposed scheme. Four 110-km 400 kv transmission lines compensated with Static Var compensator at the middle of the second terminal are interconnected. A 300-Mvar Static Var Compensator (SVC) regulates voltage on a 6,000-MVA 400-kV system. The SVC consists of a 400 kv/16-kv 333-MVA coupling transformer, one 109-Mvar THYRISTOR CONTROLLED REACTOR BANK (TCR) and 94-Mvar Thyristor Switched Capacitor banks (TSC1 2386

3 TSC2 TSC3)of three number are connected on the secondary side of the transformer. The scheme is evaluated using 400KV, 50Hz four terminal transmission system whose line parameters with values R 0=0.1888Ω/km, R 1=0.02Ω/km, L 0=3.5Mh/km, L 1=0.94mH/km, C 0=0.0083μf/km., C 1=0.012μf/km. 16KHZ sampling frequency is used to capture the high frequency current signals.the system is modeled in Matlab Simulink software. The network is simulated with matlab for different fault situations. Exhaustive simulations are carried out for L-G, L-L, L-L-G, L-L-L faults that are occurring at various locations along the paths of Terminal 1 to 2, Terminal 2 to 3, Terminal 3 to 1, and Terminal 4 to 1. For each type of fault at a particular location, the fault inception angle is varied to analyze the performance of the proposed scheme. The fault resistance value of 5 ohms also being considered. The detail D1 coefficients are used for detection and classification of the type of fault after Synchronized sampling of three phase currents at all terminals are carried out with Bior1.5 mother wavelet to obtain the coefficients (D1 1) at terminal 1 over a moving window of half cycle length by analyzing the three phase currents of the local terminal. These D1 1 coefficients are further transmitted to the remote end. The detailed coefficients received from the remote end at bus2 (D1 2) that are subtracted from the local coefficients (D1 1) to obtain effective D1 coefficients (D1 E). The Fault Index (I f1) of each E =Σ D1 phase is calculated form the expression If1 The performance of the scheme in detecting and classifying the faults i.e. line(l)-to -ground, line-to-line(l), line-line-toground(l-l-g), triple-line-to- ground(lll-g) is evaluated. In all the cases, the theory is able to detect the faults. The fault inception angle is varied from 20 0 to for all kinds of faults. The simulations shows that the fault inception angle has a considerable effect on the phase current samples, & Wavelet Transform output of post-fault signals. IV. FAULTY PHASE DETECTION AND IDENTIFICATION Figure 4Variation of fault indices of three phase currents for A-G fault at terminal 1 A) with fault Figure 5Variation of fault indices of three phase currents for A-B fault at terminal 1 A) with fault Figure 6Variation of fault indices of three phase currents for A-B-G fault at terminal 1 A) with fault Figure 7Variation of fault indices of three phase currents for A-B-C fault at terminal 1 A) with fault Figure 2 Three phase current waveform at terminal -1 Figure 3.phase currents(ia, Ib, Ic) at terminal-1 Figure 8Variation of fault indices of three phase currents for A-G fault at terminal 1 A) at 60km B) at 100km 2387

4 Figure 14Variation of fault indices of phase A & B currents at all terminals for A-B-G fault at 60km from terminal 1 A) with fault Figure 9Variation of fault indices of three phase currents for A-B fault at terminal 1 A) at 60km B) at 100km Figure 15Variation of fault indices of phase A, B & C currents at all terminals for A-B-C fault at 60km from terminal 1 A) with fault Figure 10Variation of fault indices of three phase currents for A-B-G fault at terminal 1 A) at 60km B) at 100km Figure 11Variation of fault indices of three phase currents for A-B-C fault at terminal 1 A) at 60km B) at 100km VI. FAULTY TERMINAL IDENTIFICATION Figure 12Variation of fault indices of phase A currents at all terminals for A-G fault at 60km from terminal 1 A) with fault Figure 13Variation of fault indices of phase A & B currents at all terminals for A-B fault at 60km from terminal 1 A) with fault Figures 4-7 illustrates the variation of fault indices of 3- phase currents with fault inception angle at a distance of 60 km and 100 km from Terminal-1 towards the path of Terminal-1 and Terminal-2 for A-G, A-B, A-B-G, A-B-C faults. Figures 8-11 illustrates the variation of fault indices with distance at a fault inception angle 60 0 and from first terminal to second terminal for similar type of faults. In both the cases, it is observed that the fault indices of faulty phase are large as compared with that of healthy phase. Thus the numbers of faulty phases are determined by comparing the Fault Indices with a Threshold value which is taken as 400. Once the faulty phase is detected, then the faulty terminal is detected by taking into consideration the fault indices of that particular phase at all terminals and comparing the indices obtained at all the terminals, and faulty terminal indices of that particular phase are higher than the index values of the same phase at the remaining terminals. Figures illustrate the variation of fault index of phase -A current at all the terminals for A-G fault, fault indices of phases A and B for A-B and A-B-G faults, fault indices of A,B,C phases for (A-B-C) fault at a fault inception angle of 60 0 and with variation in distance from Terminal-1 to Terminal-2, it is detected that the fault indices of that particular phase(s) at faulty terminal are higher as when compared with that of other terminals. Figures illustrate the variation of fault index of phase A current at all the terminals for A-G fault, fault indices of phases A, B for A-B and A-B-G faults, fault indices of phases A,B, C for A-B-C fault at a distance of 60km and 100km from Terminal-1 towards the path of Terminal-1 to Terminal-2, it is Seen that the fault indices of that particular phase(s) at faulty terminal is(are) higher as compared with that of other terminals. Thus the numbers of faulty phases are determined by comparing the Fault Index with a Threshold value and the faulty terminal is identified by comparing the fault index of the same phase(s) for all the terminals and the faulty terminal fault index will be more than the other terminals for the same phase which identifies the faulty terminal. 2388

5 V. CONCLUSIONS The type of FACTS devices are incorporated in the transmission system based upon the mode, the conventional distance relay is likely to over reach or under reach which can be rectified by wavelet based multi-resolution analysis approach i.e., applied for fault detection effectively, classification and faulty terminal identification in multi-terminal transmission lines. The theory has been implemented for all types of faults with variations in fault inception angle and fault distance and location of SVC at all terminals. The results indicate the accuracy in fault detection, classification and faulty terminal identification. This scheme is proved to be unaffected by the presence of SVC by testing the protection scheme on the same transmission system without SVC. The proposed protection scheme is found to be fast, reliable and accurate for different types of faults on transmission lines with and without flexible AC transmission control device such as SVC with various different inception angles at different locations. Appendix Fault Indices with Variations in Distance and Fault Inception Angle Table-1 Faulty phase identification with variation of fault indices with distance at a fault inception angle of Table-II Faulty phase identification with variation of fault indices with Table-III Faulty phase identification with variation of fault indices with fault inception angle at a distance of 60 km FIA,Degrees Table-IV Faulty phase identification with variation of fault indices with fault inception angle at a distance of 100 km FIA, Degrees Table-VA Faulty terminal identification with variation of fault indices with Table-VB Faulty terminal identification with variation of fault indices with Ia,Ib at all terminals for A-B-G fault Ia,Ib,Ic at all terminals for A-B-C Fault Table-VIA Faulty terminal identification with variation of fault indices with Table-VIB Faulty terminal identification with variation of fault indices with Ia,Ib at all terminals for A-B-G fault Ia,Ib,Ic at all terminals for A-B-C Fault

6 Table-VII Faulty terminal identification with variation of fault indices with fault inception angle at a distance of 60 km from terminal Ia,Ib at all terminals for A-B-G fault Ia,Ib,Ic at all terminals for A-B-C Fault Table-VIII Faulty terminal identification with variation of fault indices with fault inception angle at a distance of 100 km from terminal-1 [7] S.N. Ghani, Digital Computer Simulation of Three- Phase Induction Machine Dynamics A Generalized Approach, IEEE Trans Industry Appl., Vol. 24, No. 1, pp , [8] S. Wade, M.W. Dunnigan and B.W. Williams, Modelling and Simulation of Induction Machine Vector Control and Rotor Resistance Identification, IEEE Trans. Power Electronics, Vol. 12, No.3, pp , [9] K.L. Shi, T.F. Chan, and Y.K. Wong, Modeling of the Three-Phase Induction Motor using SIMULINK, Record of the 1997 IEEE International Electric Machines and Drives Conference, USA, pp. 3-6, [10] K.L. Shi, T.F. Chan and Y.K. Wong, Modeling and Simulation of Direct Self Control System, IASTED International Conference: Modeling and Simulation,, pp , Pittsburgh, USA,1998. [11] N.N. Soe, H.T. T. Yee and S.S. Aung, Dynamic Modeling and Simulation of Three phase Small Power Induction Motor", World Academy of Science, Engineering and Technology, pp , [12] P. Fritzson, Principles of Object-Oriented Modeling and Simulation with Modelica 2.1. Piscataway, NJ: IEEE Press, [13] K. M. Siddiqui, K. Sahay and V.K. Giri, Health Monitoring and Fault Diagnosis in Induction Motor- A Review, International Journal of Advanced Research in Electrical, Electronics and Instrumentation Engineering, Vol. 3,No. 1, pp , [14] K.M.Siddiqui, K.Sahay and V.K. Giri, Simulation and Transient Analysis of PWM Inverter Fed Squirrel Cage Induction Motor Drives, i-manager s Journal on Electrical Engineering, Vol.7, No.3, Jan-March, Ia,Ib at all terminals for A-B-G fault Ia,Ib,Ic at all terminals for A-B-C Fault REFERENCES [1] K.M.Siddiqui, K. Sahay and V.K. Giri, Performance and Analysis of Switching Function Based Voltage Source Inverter Fed Induction Motor, International Electrical Engineering Journal, Vol. 5, No.9, pp , [2] P.C. Krause, O. Wasynczuk and S.D. Sudhoff, Analysis of Electric Machinery, IEEE Press, [3] P.C. Krause, Simulation of Symmetrical Induction Machinery, IEEE Trans. Power apparatus Systems, Vol. 84, No. 11, pp , [4] N. Mohan, T.M. Undeland and W.P. Robbins, Power Electronics: Converters, Applications, and design, John Wiley & Sons, New York, [5] R. Krishnan, Electric Motor Drives Modelling, Analysis, and Control, Prentice Hall, [6] B.K. Bose, Modern Power Electronics and AC drives, Prentice-Hall, N.J,