Development of Real time controller of a Single Machine Infinite Bus system with PSS

Transcription

1 Development of Real time controller of a Single Machine Infinite Bus system with PSS Mrs.Ami T.Patel 1, Mr.Hardik A.Shah 2 Prof.S. K.Shah 3 1 Research Scholar, Electrical Engineering Department: FTE,M.S.University of Baroda,India 2 Research Scholar, Electrical Engineering Department: FTE,M.S.University of Baroda,India 3Electrical Engineering Department,FTE, M.S.University of Baroda,India ABSTRACT A real time controller of a Single Machine Infinite Bus power system has been developed in the Matlab/Simulink environment with code composer studio v3.3 for the Improvement of the transient stability. The real time transient stability simulations are available on the proposed controller for SMIB power systems. Transient stability has been given much attention by power system researchers and planners in recent years, and is being regarded as one of the major sources of power system insecurity. This paper presents the modelling and simulation of a single machine infinite bus (SMIB) system with real time controllers using MATLAB programming with CCS. The efficiency of the developed controller has been demonstrated through the real time simulator available with code composer studio to investigate the stabilization control performance for a study SMIB power system. Keywords: Controller design, Transient stability, single machine infinite bus (SMIB) system, power system stabilizer (PSS), Code Composer Studio (CCS). 1. INTRODUCTION Power system stabilizer (PSS) controller design, methods of combining the PSS with the excitation controller (AVR), and investigation of many different input signals and the vast field of tuning methodologies are all part of the PSS topic. This Paper will focus on development of a few of the technologies and approaches, with the goal of making the case for using this type of controller to solve the low frequency inter-area oscillation problem. The gain settings of these stabilizers are determined based on the linearized model of the power system around a nominal operating point to provide optimal performance at this point. Generally, the power systems are highly nonlinear and the operating conditions can vary over a wide range. Therefore, CPSS performance is degraded whenever the operating point changes from one to another because of fixed parameters of the stabilizer. The application of a power system stabilizer (PSS) for improving the stability of power systems has received much attention [3,4,5]. Real time controller for PSS appears to be the most suitable one, due to its robustness and lower computation burden [6]. The Real time controllers could easily be constructed using a simple microcomputer (with CCS). The supplementary stabilizing signal is determined using fuzzy membership. This paper presents a real time nonlinear control of generator excitation. Control signal is given to sum point of AVR unit shown in figure 1 & will provide sufficient damping torque for synchronous generator unit with extra enhanced in rise time & settling time & maximum overshoot and finally robustness that makes it much suitable for interconnected nonlinear synchronous generators. Fig 1. Conventional system control model Volume 2, Issue 9, September 2014 Page 36

2 This paper aims for linearized Phillips-Heffron model of power system installed with Real time controller and demonstrates the application of the model in analysing the damping effect of this controller and designing a Power system stabiliser to enhance power system oscillation stability [5]. 2. POWER SYSTEM MODEL WITH SMIB. The controller design for power system stability studies requires suitable mathematical representation so as to include all significant components of power system [8]. A Single Machine Infinite Bus (SMIB) system shown in Figure 2 is considered. Fig 2. Single machine connected to a large system through transmission lines The synchronous generator is modeled as q-axis component of voltage behind transient reactance and electromechanical swing equation representing motion of the rotor. The internal voltage equation of the generator is written as, E q=[e 1 Fd -E q -(x d -x d )I d ] where, E q is the voltage behind the transient reactance, subscripts d and q represents the direct and quadrature axis of the machine, Id is the current along the d-axis. xd, xd and Tdo are d-axis synchronous reactance, transient reactance and open circuit field time constants respectively [9]. Figure 3 shows the basic structure of PSS installed with conventional control design. The electromechanical swing equation is broken into two first order differential equations and is written as, Fig 3. Block diagram Structure of PSS (3) where, Pm and Pe are the input and output powers of the generator respectively; M and D the inertia constant and damping coefficient; ωb the synchronous speed; δ and ω are the rotor angle and speed; The electrical power output is, (4) where, Vtd and Vtq are components of generator terminal voltage (Vt) and Iq is current along the q-axis. The IEEE Type ST1 excitation system is considered in this work. The dynamic model of the excitation system is where, Vref represents the steady state (reference) value of terminal voltage, KA and TA are the gain constant and time constant of exciter respectively. Block diagram of linearized Philips Heffron model of SMIB system installed which is used for this paper. 3. CODE COMPOSER STUDIO One of Real-Time Workshop build options builds a Code Composer Studio project from the C code generated and, therefore, all features provided by Code Composer Studio work to help develop the algorithm or application. Once target-specific executable is downloaded to the hardware and run it, the code runs wholly on the target and the running process can be accessed only from Code Composer Studio or from MATLAB with two powerful tools: Link for Code Composer Studio and Real-Time Data Exchange (RTDX) Link for Code Composer Studio lets use MATLAB functions to communicate with Code Composer Studio and with the information stored in memory and registers on a target. With Volume 2, Issue 9, September 2014 Page 37

3 the links, information can be transferred to and from Code Composer Studio and with the embedded objects, information about data and functions stored on the signal processor can be retrieved. Within the collection of hardware that Link for Code Composer Studio supports, some features of the link cannot be applied. This features or components are three Link for Code Composer Studio IDE Lets use objects to create links between CCS IDE MATLAB. Link for Real-Time Data Exchange Interface Provides a communication pathway between MATLAB and the signal processor. Embedded Objects Provides Object methods and properties that let access and manipulate information stored in memory and register on signal processor, or in Code Composer Studio project. Hardware-in-the-Loop Enables to write functions in MATLAB that exercise functions from project on target processor. From MATLAB, data can be generated, can be send to target, and a function C can be used to manipulate the data in the hardware. The basic functionality of CCS with Real time controller is shown in figure 4. Fig 4. Functional block Diagram of Real time controller 4. CONTROL ACTION AND REAL TIME CONTROLLER DESIGN The action of a PSS is to extend the angular stability limits of a power system by providing supplemental damping to the oscillation of synchronous machine rotors through the generator excitation. This damping is provided by a electric torque applied to the rotor that is in phase with the speed variation. Once the oscillations are damped, the thermal limit of the tie-lines in the system may then be approached. This supplementary control is very beneficial during line outages and large power transfers. However, power system instabilities can arise in certain circumstances due to negative damping effects of the PSS on the rotor. The reason for this is that PSSs are tuned around a steady-state operating point; their damping effect is only valid for small excursions around this operating point. During severe disturbances, a PSS may actually cause the generator under its control to lose synchronism in an attempt to control its excitation field. A lead-lag PSS structure is shown in Figure 5. The output signal of any PSS is a voltage signal, noted here as VPSS(s), and added as an input signal to the AVR/exciter. For the structure shown in Figure 5, this is given by Fig 5. Stabilizer Gain & Phase Compensator This particular controller structure contains a washout block, st H /(1+sT H ), used to reduce the over-response of the damping during severe events. Since the PSS must produce a component of electrical torque in phase with the speed deviation, phase lead blocks circuits are used to compensate for the lag (hence, lead-lag ) between the PSS output and the control action, the electrical torque [12]. The number of lead-lag blocks needed depends on the particular system and the tuning of the PSS. The PSS gain KS is an important factor as the damping provided by the PSS increases in proportion to an increase in the gain up to a certain critical gain value, after which the damping begins to decrease. All of the variables of the PSS must be determined for each type of generator separately because of the dependence on the machine parameters. The power system dynamics also influence the PSS values. The determination of these values is performed by using real time code composer studio with matlab simulink. The block of PSS is generated with ccs by obtaining the PIL simulation. The design requirements of PSS on Real time controller are control design specifications. It is very difficult to transform power system objectives into control design specifications. However the designed Real Volume 2, Issue 9, September 2014 Page 38

4 time power system damping controller should satisfy the following stability and performance criteria. a) A minimum damping ratio should be maintained for critical modes and greater than 0.1 for low frequency modes like inter-area modes. b) The settling time is the main damping criteria for oscillations in time domain specifications which should be lower than the desired value.c) The damping action should not deteriorate the system to unacceptable condition and should maintain the performance and stability of the system. This is because lower the damping the phase margin is reduced [13]. Design Requirements Time domain specifications: Rise Time : 5 sec Settling Time : 10 sec % Overshoot : 10 % Rise : 1 % Settling : 5 % Undershoot : 10 Step response bounds from 0 to 15seconds. The main task is to damp out the oscillations in the SMIB system by the designed Real time Controller for PSS with stabilizer parameters as a constraints with various disturbances. In addition to that the optimization algorithm should satisfy the above specified requirements for the response of speed, rotor angle and terminal voltage of the SMIB system. Settling time is considered as a main performance criteria, because, the damping of oscillations is represented through the reduction of settling time. The following Table 1 shows the main significant to the settling time, however other design requirements are more or less satisfied depends upon the optimization algorithm chosen shows the response of speed, rotor angle and terminal voltage of SMIB system with simplex and pattern search optimization tuned PSS [14]. It is observed that the oscillations are damped out and the settling time is also reduced to less than 15 seconds. To know the stability condition of SMIB system with tuned PSS the pole-zero map for the closed loop system from step to speed, rotor angle and terminal voltage for three optimization algorithm is shown in fig.6,7& 8. From the figure it is infer that the oscillations are damp out quickly and also system changed from marginal stability condition to stable system [15]. 5. RESULTS & DISCUSSION In order to investigate the performance of single machine infinite bus system has been studied with PSS, without-pss and Real time PSS cases are compared with each other. These results are presented for the rotor speed, torque variations and Angular Position of the system With Real Tim e PSS Without PSS Speed, pu Time, Sec Fig 6. Comparisons of responses for Rotor Speed variation The Response shown in fig 6, 7 & 8 respectively depicts that the oscillations are more pronounced when a system is perturbed without PSS after which it becomes stable. It is taking very large time (more than 25 sec) to settle to steady value even with 0.05 pu increase in the input value. Therefore, the performance of the system without PSS is analyzed to find the suitability of the excitation system in removing these oscillations. Volume 2, Issue 9, September 2014 Page 39

5 Torque Variations With Real Time PSS Without PSS Time, Sec Fig 7. Comparisons of responses for Torque variation The variation of angular position and angular speed with time for 0.05 pu increase in torque for negative and positive value of K5 are shown in Fig 6 and Fig. 8 respectively. The system is coming out to be stable in both the cases; however, the transients are more with negative K5 whereas the higher angular position is attained with positive K5. Angular Position, Rad With Real Time PSS Without PSS Time, Sec Fig 8. Comparisons of responses for Angular Position As the system is stable with both positive and negative K5, the limitations of without PSS are taken care by applying power system stabilizer. With Power system stabilizer the rotor mode damping ratio and damping coefficient increases with increase in exciter gain. It depicts that angular speed and angular position stabilizes to a particular value with very few oscillations by using real time PSS Table:1 Data Validation for the Analysis of Transient Stability System W/O PSS Improved With Real timepss Parameters Rise Time Peak Time Settling Time OverShoot Angular Position Torque Variations Speed Changes Angular Position Torque Variations Speed Changes Angular Position Torque Variations Speed Changes From the simulation we can conclude that real time power system stabilizer we can stabilize our system up to certain limit and maintain the synchronism between the inter connected area and protect the whole power system from cascade tripping which is very serious matter. We can also say that only using PSS we cannot maintain stability but in some cases or condition it is require using other devices to maintain stability. Nowadays static devices are widely use in system for compensation of reactive power demand and help to maintain system stability in some transient condition. Also from fig 6, 7 and 8 Angular position which indicate the angle difference between machine and the rotors speed in p.u. We can clearly see that if there is no PSS than system can t able to sustain stability and become out of step. When we use PSS system becomes stable but there is low frequency oscillation present. When we use Real time control of PSS system may stable with no low frequency oscillation. So Real time PSS more accurate compare conventional PSS. From fig 9, 10 and 11 which shows Rise Time, Peak Time and Settling Time comparisons respectively.the response of the system for the given disturbance is growing in oscillations, so that the settling time is more than 35 seconds. So a Volume 2, Issue 9, September 2014 Page 40

6 Fig 9. Rise Time Comparisons Fig 10. Peak Time Comparisons Fig 11. Settling Time Comparisons controller must be designed to make the system stable and also to improve the damping. When PSS is connected to the system it improves the stability of the system and the oscillations are reduced. The settling time is reduced less than 25 seconds as observed from graph. Among the different PSS used for in SMIB system the Real Time PSS performs better in reducing the settling time and maximum overshoot of rotor speed, torque variations and Angular Position is reduced while satisfying the time domain specifications. Volume 2, Issue 9, September 2014 Page 41

7 6. CONCLUSION & SCOPE OF FUTURE IMPLEMENTATION Control loops of the governor as well as the AVR have a crucial role in power systems control but they have a limited capability in damping transient state oscillations. Hence, this paper proposes a simple technique for design of Power System Stabilizer for damping of oscillations using Real time controller developed code composer studio based linear control design technique. The performance of different PSS is compared, based on the settling time the Real time controller based PSS performs better than conventional PSS. By this simple Real time controller PSS design technique the oscillations are damped out quickly and the stability is improved from marginally stable to completely stable system. Time domain requirements are satisfied with overall improvement in stability. However, this scheme involves updating controller parameters in real time using a system identifier which can be complicated and expensive. Hence, the economics of the process is also a constraint. Digital design of the PSS is also possible. Hence, the design of the Power System Stabilizer has a lot of scope for future research. REFERENCES [1] S. M. Radaideh, I. M. Nejdawi, and M. H. Mushtaha, "Design of power system stabilizers using two level fuzzy and adaptive neuro-fuzzy inference systems," International Journal of Electrical Power & Energy Systems, vol. 35, pp , [2] R. V. deoliveira, R. A. Ramos, N. G.Bretas, An algorithm for computerized automatic tuning of power system stabilizers, Control Engineering Practice, Vol. 18, pp , [3] R. S. Vedam and M. S. Sarma, Power Quality: VAR Compensation in Power Systems,1st ed., CRC Press, Taylor and Francis Group, [4] S. K. Wang, J. P. Chiou, C. W. Liu, Parameters tuning of power system stabilizers using improved ant direction hybrid differential evolution. International Journal Electric Power Energy System 2009; 31(1): [5] G. Cheng, L.Q. Zhan, "Simultaneous coordinated tuning of PSS and FACTS damping controllers using improved particle swarm optimization", IEEE/APPEEC, pp.1-4, March [6] H. Hassan, M. El Metwally and A. Bendary, Enhancement of FACTS stability through robust adaptive control, The International Conference on Electric Power and Energy Conversion Systems (EPECS 09), American University of Sharjah, Sharjah, UAE, November, [7] Shoulaie, M. Bayati-Poudeh, G. Shahgholian, Damping torsional torques in turbine generator shaft by novel PSS based on genetic algorithm and fuzzy logic, Jour. of Trans. on Elec. Tech. (JTET), Vol.1, No.1, pp.3-10, Winter [8] A.G.E. Abera, B. Bandyopadhyay, "Digital redesign of sliding mode control with application to power system stabilizer", IEEE/IECON, pp , Orlando, Nov [9] C. B. Vishwakarma and R. Prasad, "Order reduction using the advantages of differentiation method & factor division algorithm," International Journal of Engineering and material sciences, vol. 15, pp [10 J. Rommes and N. Martins, Computing Large-Scale System Eigenvalues Most Sensitive to Parameter Changes, With Applications to Power System Small-Signal Stability, IEEE Transactions on Power Systems, vol. 23, May [11] V. Bandal, B. Bandyopadhyay, "Robust decentralised output feedback sliding mode control technique-based power system stabiliser (PSS) for multimachine power system", IET Con. The. and App., Vol.1, No.5, pp , Sep [12] G. Shahgholian, M. Arezoomand, H. Mahmoodian, Analysis and simulation of the single machine infinite bus power system stabilizer and parameters variation effects, IEEE/ICIAS, pp , Nov [13] V. Bandal, B. Bandyopadhyay, "Robust decentralised output feedback sliding mode control technique-based power system stabiliser (PSS) for multimachine power system", IET Con. The. and App., Vol.1, No.5, pp , Sep [14] K. R. Padiyar, FACTS Controller in Power Transmission and Distribution, New Age International (P) Limited, Publishers,2007 [15] I. Kamwa, R. Grondin, and G.. Trudel. IEEE PSS2B versus PSS4B: the limits performances of the modern power system stabilizers, IEEE Trans, vol.20, pp , May [16] Liu Qian, V. Vittal, and N. Elia, LMI Pole Placement Based Robust Supplementary Damping Controller (SDC) for A Thyristor Controlled Series Capacitor (TCSC) Device, IEEE Power Engineering Society General Meeting, pp , June 2005 [17] P. Shrikant Rao, and L. Sen, Robust pole placement stabilizer design using linear matrix inequalities, IEEE Trans. on Power Systems, vol.15, pp , pp , Feb [18] P. Kundur, Power System Stability and control, McGrowHill, USA Volume 2, Issue 9, September 2014 Page 42