Analytical investigation of the use of static VAR compensators to aid damping of inter-area oscillations

Transcription

1 CINVESTAV From the SelectedWorks of A. R. Messina 1999 Analytical investigation of the use of static VAR compensators to aid damping of inter-area oscillations Arturo Roman Messina, CINVESTAV Available at:

2 JEPE 289 Electrical Power and Energy Systems 21 (1999) Analytical investigation of the use of static VAR compensators to aid damping of inter-area oscillations A.R. Messina a, *, O. Begovich M a, M. Nayebzadeh b a Cinvestav, IPN, Unidad Guadalajara, P.O. Box , 45090, Guadalajara, Jal., Mexico b Siemens AG, EV NP 2,Postfach 3220, D Erlangen, Germany. Abstract A comprehensive investigation of the use of Static VAR Compensators (SVCs) to aid damping of low-frequency inter-area oscillations in large interconnected power systems is presented. The study of inter-area oscillations and the design of controls is done using modal analysis of a linearized model of the power system. Based on this model an efficient algorithm to compute the power oscillation flow for each mode of concern is developed. This approach allows to identify the nature of oscillation patterns and provides important information needed in the application of SVCs. Controllability and observability measures are then used to assess the impact of dynamic voltage support on system damping as well as to identify optimal locations for SVCs. The influence of system structure and load effect on the SVC performance is discussed. Detailed time-domain analyses are finally performed to check the validity of the analysis and to assess the impact of dynamic voltage support on system transient behaviour Elsevier Science Limited. All rights reserved. Keywords: FACTS; Static VAR compensators; System oscillations; Inter-area mode; Controllability and observability characteristics 1. Introduction Flexible AC Transmission System (FACTS) devices are being used extensively to increase the power transfer capability of transmission systems and improve power system control [1 4]. SVCs (Static VAR Compensators), among other FACTS devices, can also aid system stabilisation, specially in cases of insufficiently damped inter-area oscillations in loosely interconnected power systems [5 7]. In recent years the potential for dynamic stability improvement by SVCs has been recognised, leading to the design of new and advanced control and protection characteristics [5 7]. While enhanced operating characteristics permit modern SVCs to achieve stabilisation objectives, the potential for undesirable interaction with other controllers is becoming a growing cause of concern [7,8]. Also, the application of multiple compensation is now being considered by several utilities to meet performance objectives, thus demanding the integration of several analytical tools to aid siting and co-ordination of controllers. Major research projects reflect current interest in this subject [2,3]. The integration of an SVC in a complex power system requires of extensive planning and performance verification studies. SVCs have the inherent capability to contribute to damping, directly by modulating terminal voltages and * Corresponding author; aroman@gdl.cinvestav.mx. indirectly through the load response to voltage changes, and the change of generators electrical output [4,5,7]. Siting constitutes a major issue to be addressed as the ability of an SVC to contribute to system damping depends strongly on network structure and the relative location of generators, loads and the SVC [2,5,7]. Moreover, SVCs must be designed to achieve stabilisation in the presence of random noise, and often, widely changing operating conditions [6,7]. This paper presents the results of an analytical investigation of the application of SVCs to aid damping of inter-area oscillations in a 110 generators and five areas model of the Mexican Interconnected System (MIS). The study of inter-area oscillations and the design of controls is done using modal analysis of a linearized model of the power system. Based on this model, an efficient algorithm to compute the power oscillation flow for each mode of concern is developed. This approach allows to identify the nature of oscillation patterns and provides important information needed in the application of SVCs and other FACTS controllers. Controllability and observability analyses are then used to assess the impact of existing SVCs on system damping as well as to identify optimal locations for new devices. System studies include the co-ordinated application of multiple SVCs and the evaluation of supplemental control actions on system damping in the MIS. Sensitivity analyses /99/$ - see front matter 1998 Elsevier Science Limited. All rights reserved. PII: S (98)

3 200 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 1. Simplified one-line diagram of the study system. of the effect of load characteristics and network configuration on SVC performance are conducted using both, eigen-analysis and frequency response studies. Detailed non-linear time domain simulations are finally performed to check the validity of the analysis and to determine the effect of dynamic voltage support on system transient behaviour. It is shown that SVCs can effectively contribute to the simultaneous stabilisation of critical system modes while providing adequate voltage control and transient stability enhancement. Fig. 2. Simplified one-line diagram of the Temascal SVC.

4 Table 1 The five slowest oscillation modes in the MIS model A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Mode Description Eigenvalue Oscillation pattern**a Dominant machines* Freq. (Hz) Inter-area mode ^ j2.575 North systems vs. south systems MTY (1.00), FAL(0.520), RIB(0.469), MZD(0.419),SYC(0.388),GPL(0.383) Inter-area mode ^ j3.663 SE and W systems vs. N and NE MTY (1.00),MZD(0.392),GPL(0.343), systems SYC(0.342),CRB(0.239) Inter-area Mode ^ j4.610 W and C systems vs. SE system SLM(1.00),MNZ(0.919), ANG(0.666), MMT(0.658), AGM(0.560) Inter-area Mode ^ j5.687 N,NE and SE systems MZD(1.00),GPL(0.407),SYC(0.309), FVL(0.243),RIB(0.194) Inter-area Mode ^ j6.015 W, C and SE systems CRL(1.00), DBO(0.514),LGV(0.388), SLM(0.339),MNZ(0.263) * Normalised to have largest entry as unity. ** SE south-eastern, W western, N north, NE north-eastern, C central. Table 2 Top modal generation power associated with inter-area modes 1 and 3* Inter-area mode 1 Inter-area mode 3 Machine group Machine Modal generation Machine group Machine Modal generation Group A MTY Group A a REC CRB Group B SLM Group B TUL MNZ INF SLM SLP MNZ Group C MMT Group C MMT MPD MPD ANG ANG TUX * Negligible contribution. Table 3 Top 5 modal power oscillation flows associated with inter-area modes 1 and 3 Inter-area mode 1 Inter-area mode 3 Transmission line Modal power flowa Transmission line Modal power flowa Guemez-ALT Temascal-PBD PRD-ALT Temascal-MID Guemez-HUI PBD-TEX LAJ-Guemez MPD-MID HUI-LAJ TUL-TEX a Normalised to have largest entry as unity. Table 4 Top 5 modal bus voltage deviations associated with inter-area modes 1 and 3 Inter-area Mode 1 Inter-area Mode 3 Busbar Modal voltagea Busbar Modal voltagea Guemez Temascal LAJ JUI HUI MID PLA PBD ESC TCL a Normalised to have largest entry as unity.

5 202 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 4. Normalised controllability measures of critical system modes w.r.t. the Temascal SVC control action. Fig. 3. Plot of real part of eigenvalues showing the effect of system contingencies with and without voltage support at Temascal. 2. System modelling The power system is represented by a component connection state model, linearized about a selected operating point. In this approach, the overall system model is obtained by combining the dynamic models of two partial subsystems, namely the machine and FACTS devices equations and the interconnecting transmission network. For a general m busbar system with r FACTS devices, the behaviour of all dynamic devices is represented in the following form [9,10] _x ˆ A S x C S Dv Bu and Di ˆ W S x Y S Dv where: x u is an n-dimensional vector of perturbed system states is an r-dimensional vector of control inputs, associated with generator AVRs (Automatic Voltage Regulators), SVCs and other FACTS controllers 1 2 Di is a 2m-dimensional vector of incremental nodal current injections in common co-ordinates Dv is a 2m-dimensional vector of incremental network bus voltages in common co-ordinates B is an n r input matrix Submatrices A S,C S, W S and Y S represent sensitivity relations of appropriate dimensions. In addition, the interconnecting transmission network is represented by the nodal current injection equations as: Di ˆ Y N Dv G N x 3 where Y N is the network admittance matrix and matrix G N appears from the representation of other FACTS devices, namely thyristor-controlled series capacitors. It should be noted that the admittance matrix Y N includes the effects of voltage dependent non-linear loads. The overall system state equation is then obtained by substituting Eq. (3) into Eqs. (1) and (2) as: _x ˆ y ˆ Ax Xr Cx iˆ1 B i u i and where B R n r, C R p n and matrix A R n n, is the state matrix defined symbolically as: A ˆ A S C S Y S Y N Š 1 G N W S 4 5 Table 5 Controllability indices Case description Load model Inter-area mode 1 Eigenvalue CIa Inter-area mode 3 Eigenvalue CIa Base case BM ^ j ^ j CP ^ j ^ j circuit ALT-PRD out BM ^ j ^ j CP ^ j ^ j Weak south-eastern Network BM ^ j ^ j CP ^ j ^ j a CI controllability index, BM - base model, CP - constant power.

6 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 5. Magnitude of transfer function between the Temascal SVC s susceptance and the SVC AVR reference voltage for various load representations. The output vector y contains input signals for the controllers, specifically real tie-line power flows and other local stabilising signals at the FACTS buses. Eigenvalue calculation is based on an Arnoldi approach for computing selected eigenvalues of the sparse unsymmetrical state matrix [10]. 3. Modal power oscillation flow In Ref. [11] the concept of modal power oscillation flow was proposed to analyse the patterns of exchange of swing oscillation energy in power systems. In this method, the relative magnitudes and phase angle of power flow associated with a given swing mode can be calculated for an arbitrary network. Also, the contribution of each machine and load to the oscillation flow can be determined. Given a power system represented by Eq. (4), the unique solution for the state equation can be expressed as [12]: x t ˆ a i ˆ Xn iˆ1 a i e l it U i ; V T i x o where V i and U i are the left and right eigenvector associated with the ith system mode, respectively and x(o) is the initial state condition. Eq. (6) allows to express the state solution as the sum of all modal contributions. Hence, bus voltage deviations associated with a given system mode can be Table 6 Effect of supplementary modulation control at Temascal SVC input signal Inter-area mode 1 Inter-area mode 3 ALT-PRD ^ j ^ j4.61 PRD-TUX ^ j ^ j4.61 Temascal-TCL ^ j ^ j4.62 MID-Temascal ^ j ^ j obtained by substituting Eq. (2) into Eq. (3) as: Dv ˆ Y S Y N Š 1 G N W S Šx Eq. (7) allows us to express bus voltage deviations as a linear combination of modal contributions and hence, can be used to obtain the incremental bus voltage deviations at the generator, load and FACTS busbars associated with each mode of interest. It should be noted that this relation involves a transformation from the eigenvalue/vector coordinates to the network D-Q reference co-ordinates as discussed in Ref. [11]. Consequently, these quantities are henceforth referred to, as modal bus voltage deviations. The contribution of each machine, load and generator to the oscillation flow can then be obtained as a function of modal voltages according to the following algorithm: 1. Calculate modal bus voltage deviations associated with critical system modes (l c i, i ˆ 1,,N) by substituting each modal component from Eq. (6) into Eq. (7) 2. Calculate modal power deviations in branches, loads and generators by expressing the real and reactive power flow in generators, transmission lines, transformers and loads in terms of the modal voltage deviations from Eq. (7). 3. Determine the dominant contribution of machines and loads in the system to the oscillation flow. Similarly identify the relative magnitude and phase angles of power oscillation flow in the oscillation process. The relative phase of modal components portrays information of the nature of oscillation patterns. The above approach provides a clear picture of the exchange of swing oscillation energy in the network and allows to identify important information of interest in the application of FACTS controllers. First, modal bus voltage deviations permit to single out busbars where voltage support is expected to be effective in enhancing damping. 7

7 204 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Moreover, the power oscillation flow can be related to the observability of system modes, as each modal component in Eq. (6) is proportional to the eigenvector contribution. Also the analysis of relative phase angles of loads and generators conveys information of the load influence on system damping. These aspects are discussed in detail in the following sections. 4. Controllability and observability analysis The effect of a FACTS controller on a given swing mode can be obtained from the analysis of controllability and observability characteristics. A quantitative measure of controllability and observability is motivated by the analysis of the distance of the dynamic model of the system to the nearest uncontrollable system (a matrix of lower rank). Following Paige [12], the system model in Eq. (4) is controllable if and only if rank (l i I A. B) ˆ n and observable if and only if rank (C T... A T l i I) ˆ n, for i ˆ 1,,n. In practice, the calculation of the rank of a matrix can be most reliably done by computing the singular value decomposition of the matrix. This involves factoring a given matrix A of order m n into a product USV T, where U is an mxn orthogonal matrix, V is an n n orthogonal matrix, and S is an m n matrix whose off-diagonal entries are all 0 s and whose diagonal elements satisfy s 1 s 2 s n 0. It can be proved that the rank of A equals the number of nonzero singular values and that the magnitudes of the nonzero singular values provide a measure of how close A is to a matrix of lower rank [13]. The above procedure can be easily extended to provide a quantitative measure of the effect of a FACTS controller on system damping. Let u j be the input to the SVC controller connected to busbar j and y k the kth output signal from the system. Then let the following matrices be defined: P i j ˆ A l i I... B j Š and 2 3 A l i I Q i k ˆ C k i where P j C n (n 1) i and Q k C (n 1) n. The Minimum Singular Value (MSV) of Pj i and the MSV of Qk j indicate the distance from the nearest singular matrix S i ˆ [A l i I]. For a given B j, the MSV of Pj i provides the degree of coupling of the jth input to eigenvalue l i. Similarly, the MSV of Qk j indicates the degree of coupling of the kth output signal from the system to the ith eigenvalue. The procedure for determining the best location for SVCs and other FACTS controllers is as follows [14]: 1. Determine critical system modes l i, i ˆ 1,,N 2. Calculate augmented matrices Pj i and Qk i for i ˆ 1,,N 8 Fig. 6. Temascal SVC susceptance and 400 kv bus voltage at Temascal for a 400 kv three-phase short circuit. 3. Calculate the singular value decomposition of Eqs. (8) and (9). The MSV of Pj i indicates the degree of coupling of the ith system mode to the SVC control input and hence provides a measure of the effectiveness of a given location on system damping. Similarly, the MSV of Qk i provides the degree of coupling of the ith input signal of the system to the SVC voltage regulator. 4. Rank placement alternatives according to controllability and observability indices. The above approach can also be used to check the impact of existent SVCs on system dynamic performance 5. Study system characteristics A simplified diagram of the study system showing main generation and transmission facilities is provided in Fig. 1. The study system represents parts of the 400, 230, 138 and 115 kv transmission network of the MIS and encompasses the interconnected operation of five regional systems. System analyses are performed on a 110 generators, 246 transmission busbars and two SVCs model of the system. In this model, the voltage dependence characteristics of static loads is represented as 70% constant current load and 30% constant impedance characteristics for both, active and reactive power. The base operating case is that used by the authors in previous studies [15]. Table 7 Effect of voltage support at Guemez Case study Inter-area mode 1 Inter-area mode 3 SVC w/o PSDC ^ j ^ j4.613 SVC with PSDC ^ j ^ j4.611

8 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 7. Relative rotor angles of machines in the northern system for a 400 kv three-phase short circuit with and without voltage support at Temascal Dynamic voltage support in the MIS model Dynamic voltage support within the study system is provided by SVCs at the Temascal and Acatlan switching stations located in the south-eastern and western areas of the MIS, respectively (refer to Fig. 1). The Acatlan SVC has a dynamic range of 200 MV, Ar (inductive) and no capacitive capability. The Temascal SVC, in contrast, has an important leverage on system dynamic behaviour as shown by a number of studies and operating experience [1,16]. A single-line diagram of the Temascal SVC is given in Fig. 2. The SVC consists essentially of four groups of thyristor controlled branches, two thyristor switched capacitor groups (TSC), one thyristor switched reactor group (TSR) and one thyristor controlled reactor group (TCR). Each of these groups has a three-phase rating of 75 MV, Ar to produce a total dynamic range of 300 MV, Ar (capacitive) to 300 MV, Ar (inductive). The SVC is connected Fig. 8. North south interface real power flow for a 400 kv three-phase short circuit with and without voltage support at Temascal. Fig. 9. Rotor angles for a 400 kv three-phase fault with and without voltage supplementary modulation control at Temascal. to the 400 kv system through a three-phase 3-winding, 100 MV Ar transformer with a 12-pulse scheme. The SVC control system includes a measuring device, a distribution unit, and an integral-based voltage controller. The input signal to the AVR is the 400 kv bus voltage obtained from the measuring device (MD). This device contains a six pulse rectifier and a low pass filter having a time constant of 1.5 ms to reduce fast transients in the 400 kv terminal voltage. Droop compensation (slope setting) is achieved by feedback of the SVC total current [1,10] as shown in Fig. 2. The output signal from the integrator is the reference susceptance B ref for the SVC. This susceptance is converted into digital signals (ON-OFF) for the TSC and TSR branches so as to mach the desired value of susceptance. The control system also includes a synchronising unit to ensure that the regulator signals are updated and that the firing pulses are given at the right instant. No supplemental modulation controls are presently used in the SVC. 6. Damping characteristics in the MIS model The MIS model exhibits two weakly damped inter-area modes at approximately 0.40 and 0.73 Hz, associated with the interaction of geographically widespread machines. Table 1 synthesises the main characteristics of the 5 slowest oscillation modes showing their associated frequencies and dominant machines as determined from the normalised speed components of the right eigenvector. The dominant mode is determined by network structure, generation pattern and load characteristics. Inter-area mode 1 involves the interaction of machines in the north systems (north and north-eastern systems) swinging coherently against machines in the western, south-eastern and central systems of the MIS. Observability of interarea mode 1 is high at machines in the north and northeastern systems, namely the generators MTY, SYC, MZD, RIB and FAL. Consequently, observability of this mode is high at the north south interface (refer to Fig. 1).

9 206 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 10. North south interface real power flow for a 400 kv three-phase fault with and without supplementary modulation control at Temascal. Also of concern, inter-area mode 3, shows the interaction of hydro generating plants located in the south-eastern network of the MIS (machines MMT, MPD, PEA and ANG) swinging against machines in the western and central areas. The observability of inter-area mode 3, appears primarily related to machines in the western and south-eastern areas and is hence highly observable in the tie-lines linking the south-eastern network with the central and western systems. Modal power flow studies were conducted to ascertain the nature of oscillation patterns in the MIS model. Table 2 shows the contribution of dominant machines (modal power generation) to inter-area modes 1 and 3. In this Table, modal generation power is expressed relative to the largest modal power flow associated with the mode in study. For the sake of clarity, participating machines in this Table are classed into three main groups showing a nearly coherent behaviour: 1. group A including machines in the north systems, 2. group B considering machines in the central and western systems, and 3. group C accounting for machines in the south-eastern network of the MIS. It should be noted that the relative phase angle of modal generation provides the relative phase of the oscillation. Clearly, the oscillation pattern follows closely the information provided by the rotor speed deviations in Table 1 but this analysis provides a clearer picture of the exchange of oscillation energy. Examination of the relative magnitudes and phase angles of power oscillation flow in Table 3 shows a close agreement with the expected system behaviour. As suggested from conventional eigen-analysis and time domain studies, transmission lines linking the north and south systems (tielines Guemez-ALT and PRD-ALT) show the largest participation on mode 1 while transmission lines linking the Fig. 11. Temascal SVC output and 400 kv bus voltage for a 400 kv threephase short circuit with and without supplementary modulation control at Temascal. south-eastern network with the central system (Temascal- PBD) show a large participation on mode 3. Also of interest, the analysis of normalised modal voltage deviations in Table 4 provides a screening of candidate locations to place shunt compensation. For inter-area mode 1, busbars close to the north south interface (busbars Guemez, LAJ,HUI, PLA,ESC) show the largest participation, suggesting that dynamic voltage support could be used to enhance damping of this mode. In contrast, the analysis of modal voltages associated with inter-area mode 3 shows a large participation of busbars on the 400 kv south-eastern network (busbars Temascal, JUI,MID,PBD,TCL). It is noteworthy that the 400 kv Temascal busbar exhibits the largest modal participation on this mode. Fig. 12. Rotor angles for a 400 kv three-phase fault with an SVC and PSDC at Guemez.

10 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 13. Bus voltages for a 400 kv three-phase fault with an SVC and PSDC at Guemez The impact of voltage support at Temascal on system damping Earlier studies [16] identified several operating conditions under which voltage support at Temascal might increase system damping. These include (i) high transfers levels from the south-eastern system to the central and north-eastern systems, and (ii) weak network configurations. The effectiveness of the Temascal SVC to influence the damping of interarea modes 1 and 3 was carefully studied for the latter case. The Temascal SVC was represented in detail in these studies. In this model, the distribution unit was represented as a simple delay. Further, the steady-state voltage current (V I characteristics) was adjusted to a 3% slope for all studies. Fig. 3 shows some selected simulations indicating the effect of dynamic voltage support on system damping for various network and operating conditions. As shown, a number of contingencies have the potential to affect damping of critical modes. It is also of significance that the loss of voltage support at Temascal (case 2) can have a significant impact on the damping characteristics of mode 3 as expected from previous analyses. A number of additional studies confirmed that voltage support at Temascal plays a critical role to enhance system dynamic characteristics under weak operating conditions. The ability of the Temascal SVC to aid damping of critical modes was additionally studied using controllability analysis. Controllability indices associated with the 5 slowest system modes are presented in Fig. 4. This analysis reveals that the Temascal SVC has an important influence on inter-area mode 3 and to a less extent on modes 1, 5 and 2 suggesting the need for supplemental modulation control. It is worth nothing that these studies correlate well with the analysis of modal voltage deviations in Table Influence of load characteristics SVCs can aid damping directly by modulating terminal Fig. 14. North south interface real power flow for a 400 kv three-phase fault with an SVC and PSDC at Guemez voltages and indirectly through the effect of loads and other controllers on machines outputs. To investigate the effect of load on SVC performance, the frequency response for the transfer function between the SVC s susceptance (Db svc ) and the SVC s AVR input (DV ref ) was calculated for several operating conditions. The analysis of the transfer function response in Fig. 5 shows large peaks around the frequency of inter-area modes 1, 3 and 5. Here a large peak implies that the SVC s susceptance will be more sensitive to terminal voltage variation for that particular frequency [17]. This approach provides also a clearer picture of the control response for various network configurations and load characteristics and permits to determine undesirable control interaction with other devices. Clearly, loads approaching the constant power behaviour tend to produce the largest SVC response for all cases examined. A similar behaviour was observed for other operating conditions. Controllability analyses were further conducted to verify the influence of load characteristics in the ability of the SVC to contribute to damping. Table 5 synthesises some few simulations showing the impact of load on the controllability of modes 1 and 3. Controllability indices are expressed relative to the base case controllability index associated with inter-area mode 3. These studies demonstrate that the SVC becomes more effective to enhance damping for the weakest operating conditions. It is also interesting to observe that controllability of critical modes generally decreases when load characteristics approach that of a constant power model The effect of supplemental modulation control at Temascal A simple power system damper controller (PSDC) was chosen to assess the impact of voltage modulation at

11 208 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Fig. 15. Simplified SVC model. Temascal on system damping (refer to Appendix). The PSDC consists of a wash-out stage, a double lead-lag stage and a filter to attenuate low-frequency components. Several different supplementary modulating signals were tested from observability analyses but no specific efforts to optimise the setting of controllers were undertaken at the present stage of this research. Table 6 shows the effect of supplemental modulation on the damping of critical modes for various input signals. The use of supplementary signals is found to provide an effective contribution to system damping particularly for inter-area modes 1 and 3. Instances are shown however, where a given input signal could impair damping of these modes. Among the several input signals analysed, tie-line power-based signals proved more desirable than other alternatives; this fact was further confirmed from observability analyses Effect of multiple shunt compensation The procedure developed in Section 4 was applied to determine the SVC 0 s optimal locations. Controllability measures pinpointed busbars on the south-eastern network as the most effective alternatives to enhance damping of mode 3. Conversely busbars close to the north south interface appeared from these studies as the most effective options to enhance the damping of mode 1. On this basis, the Guemez switching station on the north-eastern system was initially selected for placement of compensation. A ^ 200 MV, Ar TSC/TCR SVC was selected but no specific studies to determine optimal sizing were performed. Again a simple PSDC was chosen for all simulations. The input to the modulation controller is the tie-line real power flow across the north south interface selected form observability analyses. Table 7 shows the effect of this SVC on the damping of inter-area modes 1 and 3. It can be seen that this SVC can provide a significant contribution to the damping of inter-area mode 1. As expected, no noticeable impact is appreciated on mode Impact on transient performance Transient stability studies have been performed to determine the effects of dynamic voltage support on system dynamic behaviour. To this purpose, several system perturbations were investigated that excite critical system modes. Figs. 6 8 present the system response for a 400 kv threephase short circuit at the substation TEX in the central system. This fault causes severe oscillations at several machines. Also, undamped oscillations are observable in the north south interface as shown in Fig. 8. It can also be seen that the SVC at Temascal provides effective stabilisation of the 400 kv network thus indirectly enhancing dynamic performance. The analysis of rotor angle swings in Fig. 7 reveals that voltage support can effectively contribute to improve damping of remote machines. Moreover, the SVC aids damping of power oscillation at the north south interface. Other studies showed a positive contribution on the damping of other machines. While SVC constant reference voltage constant at Temascal was found to enhance damping, the use of supplemental modulation control was investigated. The supplementary signal was chosen from the analysis of observability measures. Cases of interest include: 1. the use of a PSDC using real power from the transmission line from MPD to MID (case a), and 2. the use of real power from ALT-PRD as supplementary signal (case b).

12 A.R. Messina et al. / Electrical Power and Energy Systems 21 (1999) Figs. 9 and 10 show the effect of supplemental control on system damping. Clearly, the use of modulation control provides additional damping in rotor swings of critical machines as well as increased damping of real power oscillation flow at the north south interface. As expected, modulation control can have a deleterious effect on dynamic voltage regulation around the Temascal busbar as shown in Fig. 11. A number of studies were finally undertaken to assess the impact of multiple shunt compensation on systemwide damping. Figs show the impact of installing a second SVC at Guemez. Fig. 15 depicts the SVC model used in these studies. System dynamic enhancement is manifested in additional damping of rotor angle swings at machines on the north-eastern system and a better damped power transfer across the north south interface. Other studies suggest that voltage support at Guemez could play a vital role on small signal stability and voltage stability for higher power transfers across this interface. 8. Summary and conclusions A comprehensive study of the application of SVCs to enhance damping of inter-area oscillations has been presented. Application studies on the MIS show that SVCs can have an important influence on system-wide damping and on the improvement of dynamic performance. The ability of an SVC to contribute to damping depends strongly on the relative location of generation, load and the SVC. In complex systems, this mechanism of interaction can be rather complicated. Eigen-analysis and modal power flow studies can provide a clear picture of the exchange of oscillation energy and to aid understanding of the mechanism by which SVCs contribute to damping. Location plays the first natural role on their ability to contribute to damping. Hence, appropriate techniques to measure the effectiveness of different placement alternatives are desirable. Controllability and observability measures have been used in this research to determine optimal location for SVCs as well as to understand the impact of existent devices on system-wide damping. These measures are thought to be useful for this purpose but their calculation involves repetitive simulations for each compensation alternative. Other tools such as modal power flow studies can be used to screen candidate alternatives on which perform more detailed studies. Constant reference voltage control has been found to be effective in increasing transmission capabilities and, at the same time, allow a significant contribution to damping. As with other controllers, the effectiveness of an SVC to contribute to damping is expected to be affected by the operating point. This aspect however, has not been properly addressed. Other system studies demonstrated that dynamic voltage support by means of SVCs becomes more effective to enhance damping under high stress or weak operating conditions. Conversely, load characteristics approaching a constant power behaviour are revealed to limit the effectiveness of voltage support on system damping. This mechanism is not fully understood and deserves further investigation. The use of supplementary modulation control functions can significantly enhance damping of critical inter-area modes. The design of the controllers requires knowledge of observability characteristics and expected operating conditions. The co-ordinated application of SVCs including tuning of controllers is to be further investigated. References [1] Aboytes F, Arroyo G. Application of static VAR compensators in longitudinal power systems. IEEE Trans. on Power Apparatus and Systems 1983;PAS-102(10): [2] Larsen, E.V., Chow, J.H., SVC control design concepts for system dynamic performance. Application of Static VAR Systems for System Dynamic Performance. IEEE Publication 87th PWR (1987) [3] IEEE Power Engineering Society, FACTS Applications, IEEE Special Publication 96TP116-0 (1996). [4] Larsen EV, Clark K, Hill AT, Piwko RJ, Beshir MJ, Bhuiyan M, Braun K. Control design for SVC s on the Mead-Adelanto and Mead-Phoenix transmission project. IEEE Trans. on Power Delivery 1996;11(3): [5] Olwegard A, Walve K, Waglund G, Frank H, Torseng S. Improvement of transmission capacity by thyristor controlled reactive power. IEEE Trans. on Power Apparatus and Systems 1981;PAS- 101(8): [6] Larsen EV, Sanchez-Gasca JJ, Chow JH. Concepts for design of FACTS controllers to damp power swings. IEEE/PES 1994, Summer Meeting San Francisco CA Paper 94 SM PWRS. [7] Paserba JJ, Larsen EV, Grund CE, Murdoch A. Mitigation of interarea oscillations by control. IEEE Winter Power Meeting, Symposium on Inter-Area Oscillations February (1991) [8] Larsen EV, Rostamkolai DA, Fisher DA, Poitras D. 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