POWER SYSTEM STABILITY IMPROVEMENT WITH FACTS CONTROLLERS

Abstract

This thesis mainly contributes in the area of application of various Flexible AC Transmission Systems (FACTS) controllers for power system stability improvement ensuring secure and stable operation of the power system. In this context, modern heuristic optimization techniques are employed to design the FACTS-based controllers and also to find the optimal location of FACTS controllers. In recent years, one of the most promising research field has been "Heuristics from Nature", an area utilizing analogies with nature or social systems. Among these heuristic techniques, Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and GA-based multiobjective optimization techniques appeared as promising algorithms for handling the optimization problems. In the present study, an attempt has been made to explore the application of these modern heuristic optimization techniques to improve the stability of a power system installed with FACTS controllers. The main objectives ofthe proposed research work are; 1. Application and comparison of modern heuristic optimization techniques in FACTS-based controller design. 2. Development of MATLAB/SIMULINK models for power systems with both FACTS controllers andpower system stabilizer andtheir coordinated design. 3. Determination of optimal location ofFACTS controllers. 4. Investigations on power system stability improvement using FACTS controllers and further extended to distribution networks embedded with wind energy. Optimization techniques such as Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) are inspired by nature, and have proved themselves to be effective solutions to optimization problems. Since the two approaches are supposed to xxxm find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. Both PSO and GA optimization techniques have been applied for designing a Thyristor Controlled Series Compensator (TCSC)-based controller. The design objective is to enhance the stability of a power system following a disturbance. Phillips-Herffron model of a Single- Machine Infinite-Bus (SMIB) power system equipped with TCSC controller is used to model the system in these studies. The design problem is formulated as an optimization problem and both PSO and GA optimization techniques are employed to search for optimal controller parameters. The performance of both optimization techniques in terms of computational efforts, computational time and convergence rate is compared on a weakly connected power system subjected to different disturbances. Further, the performance of the GA based TCSC controller and PSO-based TCSC controller are analyzed and compared with a conventional Power System Stabilizers (PSS). The eigenvalue and non-linear simulation results are used to show the effectiveness of both the techniques in designing a TCSC-based controller, to enhance power system stability. PSSs are now routinely used in the industry to damp out oscillations. The problem of FACTS controller parameter tuning in the presence of PSS is a complex exercise as uncoordinated local control of FACTS controller and PSS may cause destabilizing interactions. To improve overall system performance, PSSs and FACTS power oscillation damping controller should operate in coordinated manner. In view of the above, to avoid adverse interactions, PSS and TCSC-based controllers are simultaneously designed. To compare the capability of PSS and TCSC-based controller, both are designed independently first and then in a coordinated manner for individual and coordinated application. The proposed controllers are tested on a weakly connected XXXIV power system. The eigenvalue analysis and nonlinear simulation results are analyzed to show the effectiveness of the coordinated design approach over individual design. There has beenmuch research interest in developing newcontrol methodologies for increasing the performance of the power system subjected to a disturbance. The majority of these control methodologies concerns improvement of only one type of stability performance; either improving the oscillatory stability performance (reflected in the deviation in generator rotor angle) or the system voltage profile. Obviously, the main purpose of design of a FACTS-based controller is to enable it to improve the overall system performance. Design of such kind of controllers is inherently a multiobjective optimization problem. Multi-objective optimization problems usually have no unique or perfect solution, but a set of alternative solutions, known as the Pareto optimal set. With these concerns in mind, a multi-objective GA approach is employed to determine Pareto solution set for a TCSC-based controller design and latter the approach is extended for coordinated design of TCSC and PSS. Small disturbance analysis requires linearization of the system model and which may not properly capture the complex dynamics of the system, especially during major disturbances. This presents difficulties for tuning the FACTS controllers, so the controllers tuned to provide desired performance at small disturbance condition do not guarantee acceptable performance in the event of major disturbances. In the proposed research work, to optimize the TCSC-based controller parameters under large disturbance condition, model of the SMIB power system with TCSC controller is developed in the MATLAB/SIMULINK environment and the TCSC controller parameters are optimized underthe most severe three-phase fault conditions. Twotypes of synchronous generator models are considered e.g. generator with main field winding (model 1.0) and generator with field circuit and one equivalent damper on q-axis xxxv (model 1.1). A detailed analysis on the selection of objective function and controller structure for the efficient operation of the TCSC-based controller is being carried out suitably. Different controller structures (proportional-integral-derivative and lead-lag structure) and various objective functions (integral square error and integral of timemultiplied absolute value of the error) are used in the analysis and important conclusions are derived based on the non-linear simulation results. Further, a PSS is also included in the developed model and PSS and TCSC-based controllers are simultaneously designed. The effectiveness of the developed model with the proposed controllers are tested under various large disturbance (three-phase fault, line outage) and small disturbance (increase/decrease in mechanical power input and reference voltage settings) as well as under different operating conditions. Further, the approach is extended for a three-machine nine-bus power system installed with a TCSC. The location of the TCSC controller in multi-machine power system is so chosen that it improves the transient stability of the system for the most severe situation where the critical fault clearing time is minimum. A comprehensive assessment of the effects of Static Synchronous Series Compensator (SSSC)-based controller in improving the power system stability has been carried out in the present study. The performance of the proposed controller is evaluated under various large and small disturbance conditions for both SMIB system and multimachine power system. In addition, a multi-objective GA approach is also employed to generate Pareto solution set in SSSC-based controller design. The design objective is to improve the transient performance of a power system subjected to a severe disturbance for a power system installed with a SSSC. A fuzzy-based approach is applied to select the best compromise solution from the obtained Pareto set. The results show the effectiveness of the evolutionary algorithm tools for handling multi-objective xxxvi optimization problems, where multiple Pareto optimal solutions can be found in one simulation run. Further, coordinated design of PSS and SSSC-based controller for both single-machine infinite-bus and multi-machine power system has been carried out. Simulation results are presented and analyzed under wide variation in operating conditions and disturbance to show the effectiveness of the coordinated design approach. It has been observed that shunt FACTS controllers give maximum benefit from their stabilized voltage support when sited at the mid-point of the transmission line. The proof of maximum increase in power transfer capability is based on the simplified model of the line that neglects the resistance and capacitance, which is quite a reasonable assumption for short transmission lines. However, for long transmission lines with pre-defined direction of real powerflow, the results maydeviate significantly from those found for the simplified model, especially with respect to transient stability improvement. In this thesis, a systematic procedure is proposed to determine the optimal location of single and multiple Static Synchronous Compensators (STATCOM) for transient stability improvement. Minimization of the rotor angle difference satisfying the stability criteria following a severe disturbance is formulated as an optimization problem and the optimal location is searched employing GA. A two-area test system is used to show the effectiveness of the proposed method for determining the optimal location. The effect of different line power flows and the generator loadings on optimal location is also investigated. The results show that, by changing the location of shunt FACTS controllers, transient stability can be improved. It is also observed that the optimal location depends on the line loading and initial operating conditions of the system. Then, coordinated design problem of STATCOM-based controller with multiple power system stabilizers (PSS) is formulated as an optimization xxxvn problem and optimal controller parameters are obtained using PSO. The coordinated design problem is also extended to a four-machine two-area system and the results show that the inter-area and local modes of oscillations are well damped with the proposed approach. Finally, a comprehensive study about the stability performance improvement of a distribution network embedded with wind energy and a STATCOM is presented. The dynamic behavior of distribution system, during an external three-phase fault and under various types of wind speed changes, is investigated. The study is carried out by threephase, non-linear, dynamic simulation of distribution system component models. Simulation results are presented for two control strategies of STATCOM (namely the voltage and the var control mode), and four types of wind speed (namely constant wind speed, linear change of wind speed, gust change of wind speed and random change of wind speed) changes. It is observed that, the FACTS-based reactive power compensation prevents large deviations of bus voltage magnitude induced by reactive power drawn from distribution network by wind farms and helps in maintaining the system stability. It is also noticed that, after being subjected to an external fault, the var control mode is more effective in maintaining the system stability so that the Wind Turbine Induction Generators (WTIG) remain connected to the distribution system running at a speed corresponding to the system frequency. However, the variation in terminal voltage magnitude is less when the STATCOM is operated under voltage control mode compared to the var control mode. In summary, the present work contributes in the area of power system stability and its improvement using FACTS controllers. Modern heuristic optimization techniques have been employed to determine the optimal location, design the FACTSbased controllers and simultaneous tuning of FACTS-based controller and PSS. XXXVlll Overall, the results indicate that both PSO and GA algorithms can be used for parameter optimization of FACTS-based controller, its coordinated design with PSS and also for determining the optimal location. It is observed that, in terms of computational time, the GA approach is faster. The computational time increases almost linearly with the number of generations for both GA and PSO, but for PSO the computational time increases more rapidly with the number of generations. However, the PSO seems to arrive at its final parameter values in fewer generations than the GA. In case of multi-objective optimization approach for generating Pareto solutions, the decision makers has the choices and can choose from the solutions in the Paretooptimal set to find out the best solution according to the requirement and needs as the desired parameters of their controllers.