Power System Stability Enhancement Research Articles

Takagi-Sugeno Fuzzy Gains Scheduled PI Controller for Enhancement of Power System Stability

Problem statement: Power system oscillations affect system stability and may lead to failure if not properly controlled. Approach: A Takagi-Sugeno Fuzzy Gains Scheduled Proportional and Integral (FGPI) controller was proposed for a Thyristor Controlled Series Capacitor (TCSC)-based stabilizer to enhance the power system stability. Linguistic rules and fuzzy inference mechanism are utilized to tune the controller parameters on-line in different operating states. The proposed controller was applied to a single machine infinite bus system represented by the Phillips-Heffron generator model. Simulation studies have been carried out using MATLAB Fuzzy Logic toolbox. Simulated Annealing-based Power System Stabilizer (SAPSS) and Simulated Annealing-based TCSC Stabilizer (SACSC) approaches were also simulated in this study and their results were compared with proposed controller. Results: The simulation results demonstrated that the proposed control scheme performs well and strongly control the power system under different loading conditions, disturbances and system parameter variations. Conclusion: The proposed controller is robust and more suitable for damping of low frequency oscillation and more effective in improving dynamic stability and voltage profile than the two other approaches.

Implementation of Bio Inspired Genetic Optimizer in enhancing Power System Stability

The phenomenon of Stability of Modern Power Systems has received a great deal of attention in recent years. With the increasing complexity of the Modern Power Systems, the system stability is affected by Low frequency oscillations produced in the system. This paper provides a systematic approach to design a damping controller to damp the oscillations based on Bio inspired Genetic Algorithm(GA).The design problem is formulated as an Multiobjective Optimization criterion comprising of Eigen value based and Time domain based objective functions to compute the optimal controller parameters. The main objective here is to shift the closed loop eigen values to better positions in s plane and also to minimize the integral squared error involving rotor speed and power angle deviations so that the system stability will be enhanced to a greater extent. To validate the effectiveness and robustness of the proposed controller, Non linear simulations has been implemented under various system operating conditions and also introduction of disturbances in the form of outage of Transmission line in the system considered. The proposed controller design is also compared with the conventional Lead lag controller design to show the importance of the proposed Bio inspired controller design.

Application of Multi-Objective PSO Algorithm for Power System Stability Enhancement by Means of SSSC

Application of Multi-Objective PSO Algorithm for Power System Stability Enhancement by Means of SSSC

Application of adaptive Lyapunov-based UPFC supplementary controller by neural network algorithm in multi-machine power system

In this paper, a new adaptive unified power flow controller (UPFC) based on the Lyapunov method and neural network structure is presented. The corresponding energy function is derived for the single machine infinitive bus system with classic generator model representation. Damping control strategy to improve transient behavior of the system is determined by considering the dynamic modeling of the UPFC. The Lyapunov-based controller is extended to interconnected power system by considering the two-machine equivalent model and the center of inertia concept. The recurrent neural network (RNN) with back propagation algorithm is also used to overcome the uncertainty issues and also to consider the more detailed power system. The designed Lyapunov-RNN-based controller is applied to the interconnected power system between the Esfahan–Yazd region transmission network in Iran power system. The performance of the proposed controller is compared with other different controllers by applying some disturbances in the system. Finally, simulation results are presented and the effectiveness of the proposed method for power system stability enhancement is discussed as well.

Differential evolutionary algorithm for TCSC-based controller design

In this paper, a systematic procedure for modelling, simulation and optimal tuning the parameters of a thyristor controlled series compensator (TCSC) controller, for the power system stability enhancement is presented. The design problem of the proposed controller is formulated as an optimization problem and differential evolution (DE) is employed to search for optimal controller parameters. A detailed analysis on the selection of objective function and controller structure on the effectiveness of the TCSC controller is carried out and simulation results are presented. The dynamic performance TCSC controller under various loading and disturbance conditions are analyzed and compared. Finally, the proposed design approach is extended to a multi-machine power system for simultaneous design of multiple and multi-type controllers.

Design and Analysis of Robust SMES Controller for Stability Enhancement of Interconnected Power System Taking Coil Size Into Consideration

In power applications, efficiency and effectiveness of SMES with proper control are promising and highly remarkable, however, quite costly. Accordingly, optimum design and utilization are essentially needed. This paper presents the design and analysis of robust SMES controller for stability enhancement of interconnected power system taking coil size into consideration. With lead/lag controller structure, parameters of robust SMES controller can be optimized by a metaheuristic method; meanwhile, a multiplicative uncertainty is included in the design to cope with system uncertainties. Lastly, aiming at achieving optimum design and utilization, robust controllers for SMES with different coil sizes are examined to investigate performance and robustness under different situations via simulation studies.

Enhancement of transient stability by fuzzy logic-controlled SMES considering communication delay

This paper presents a fuzzy logic-controlled superconducting magnetic energy storage (SMES) for the enhancement of transient stability in a multi-machine power system. The control scheme of SMES is based on a pulse width modulation (PWM) voltage source converter (VSC) and a two-quadrant DC–DC chopper using gate-turn-off (GTO) thyristor. Total kinetic energy deviation (TKED) of the synchronous generators is used as the fuzzy input for SMES control. Communication delays introduced in online calculation of the TKED are considered for the actual analysis of transient stability. Global positioning system (GPS) is proposed for the practical implementation of the calculation of the TKED. Simulation results of balanced fault at different points in a multi-machine power system show that the proposed fuzzy logic-controlled SMES is an effective device for transient stability enhancement of multi-machine power system. Moreover, the transient stability performance is effected by the communication delay.

Stability enhancement of power system by simultaneous ac-dc power transmission

Generators may supply power to infinite bus through a single circuit long ac transmission line. The system becomes unstable after the clearance of a fault if the pre fault power transfer or the fault clearance time is high. Conversion of the line for simultaneous ac-dc power flow may keep the system stable with high values of pre fault power and fault clearance time. During the transient period after the clearance of the fault, ac power flow is switched off and the dc power flow is augmented to produce a retarding torque to bring back the generator to its normal speed. Fast control of dc current regulator may be used for this purpose. The circuit breakers are then reclosed and the ac power flow is resumed at its pre fault value without any oscillation. The power swing is low and the system is optimally damped at the end of first swing.

Innovation on Energy Power Technology (20)Development of Self-commutated Static Var Compensator (STATCOM) and its Practical Application

The self-commutated Static Var Compensator (STATCOM) is expected as one of the most effective tools to enhance power system stability and has been applied world-widely in recent years. Since the first prototype of STATCOM was developed in Japan in 1980, continual efforts by utilities and manufactures drove the development forward to the practical application of STATCOM, resulting in the world-first application of 80MVA STATCOM using GTO thyristors in 1991, followed by the 80MVA STATCOM using GCT thyristors in 2003. Since then, the application of STATCOM has been extended to not only power utility systems but also industrial systems. This paper describes historical development events and engineer's efforts to develop the STATCOM, including some episodes.

APPLICATION OF GENETIC ALGORITHM FOR PSS AND FACTS-BASED CONTROLLER DESIGN

This paper investigates the application of genetic algorithm (GA) for the design of a power system stabilizer (PSS) and a flexible ac transmission system (FACTS)–based controller to enhance power system stability. The design problem of the proposed controllers is formulated as an optimization problem and the GA optimization technique is employed to search for optimal controller parameters. The proposed controllers are tested on a weakly connected power system under various disturbances and loading conditions, and compared with a conventional PSS (CPSS). The eigenvalue analysis and nonlinear simulation results show the effectiveness and robustness of the proposed controllers.

Rough Fuzzy Control of SVC for Power System Stability Enhancement

This paper presents a new approach to the design of a rough fuzzy controller for the control loop of the SVC (static VAR system) in a two area power system for stability enhancement with particular emphasis on providing effective damping for oscillatory instabilities. The performances of the rough fuzzy and the conventional fuzzy controller are compared with that of the conventional PI controller for a variety of transient disturbances, highlighting the effectiveness of the rough fuzzy controller in damping the inter-area oscillations. The effect of the rough fuzzy controller in improving the CCT (critical clearing time) of the two area system is elaborated in this paper as well.

Transient Stability Enhancement of Power Systems by Lyapunov-Based Recurrent Neural Networks UPFC Controllers

A Lyapunov-based recurrent neural networks unified power flow controller (UPFC) is developed for improving transient stability of power systems. First, a simple UPFC dynamical model, composed of a controllable shunt susceptance on the shunt side and an ideal complex transformer on the series side, is utilized to analyze UPFC dynamical characteristics. Secondly, we study the control configuration of the UPFC with two major blocks: the primary control, and the supplementary control. The primary control is implemented by standard PI techniques when the power system is operated in a normal condition. The supplementary control will be effective only when the power system is subjected by large disturbances. We propose a new Lyapunov-based UPFC controller of the classical single-machine-infinite-bus system for damping enhancement. In order to consider more complicated detailed generator models, we also propose a Lyapunov-based adaptive recurrent neural network controller to deal with such model uncertainties. This controller can be treated as neural network approximations of Lyapunov control actions. In addition, this controller also provides online learning ability to adjust the corresponding weights with the back propagation algorithm built in the hidden layer. The proposed control scheme has been tested on two simple power systems. Simulation results demonstrate that the proposed control strategy is very effective for suppressing power swing even under severe system conditions.

Power Supply Reliability Assessment in UPFC-installed Transmission System for ATC Enhancement Considering Transient Stability

With recent development of power electronics technology, power system stability enhancement and optimal power flow control by using Flexible AC Transmission System (FACTS) devices have so far been studied. The FACTS devices to relieve multiple constraints can also make it possible to enhance Available Transfer Capability (ATC) without construction of new transmission lines. The previous research revealed that ATC is expanded by avoiding multiple constraints in OPF using Unified Power Flow Controller (UPFC). For long-term operation of such ATC-expanded power system, it is necessary to evaluate power system reliability. In this paper, the evaluation method of supply reliability for UPFC-installed power system is proposed. Both thermal capacity and transient stability constraints are considered. The effectiveness of the proposed method is shown by numerical examples for IEEJ East10-machine test system.

Supplementary Damping Controller Design using Direct Heuristic Dynamic Programming in Complex Power Systems

In modern, large scale interconnected power grids, low-frequency oscillation is a key roadblock to improved power transmission capacity. Supplementary generator control, flexible AC transmission system (FACTS), and high voltage direct currents (HVDC) are engineered devices designed to damp such low frequency swings. In this paper a neural network-based approximate dynamic programming method, namely direct heuristic dynamic programming (direct HDP), is applied to power system stability enhancement. Direct HDP is a learning and approximation based approach to addressing nonlinear system control problems under uncertainty, and it is also a model-free design strategy. The action and critic networks of the direct HDP are implemented using multi-layer perceptrons; learning is carried out based on the interactions between the controller and the power system. For this design approach, real time system responses are provided through wide-area measurement system (WAMS). The controller learning objective is formulated as a reward function that reflects global characteristics of the power system under low frequency oscillation, as well as tight coupling effects among system components. Direct HDP control design is illustrated by case studies, which are also used to demonstrate the learning control performance. The proposed direct HDP learning control is also developed as a new solution to a large scale system coordination problem by using the China Southern Power Grid as a major test bed.

Robust coordinated design of excitation and STATCOM-based controller using genetic algorithm

Power system stability enhancement via robust coordinated design of a power system stabiliser (PSS) and a static synchronous compensator (STATCOM)-based stabiliser is thoroughly investigated in this paper. The coordination among the proposed damping stabilisers and the STATCOM internal AC and DC voltage controllers as well as the current regulator has also been taken into consideration. The coordinated design problem is formulated as an optimisation problem with a time-domain simulation-based objective function and genetic algorithm (GA) is employed to search for optimal controller parameters. The proposed stabilisers are tested on a weakly connected power system with different disturbances and loading conditions. The non-linear simulation results show the effectiveness and robustness of the proposed control schemes over a wide range of loading conditions and disturbances. Further, the proposed design approach is found to be robust and improves stability effectively even under small disturbance and unbalanced fault conditions.

Comparison of particle swarm optimization and genetic algorithm for FACTS-based controller design

Recently, genetic algorithms (GA) and particle swarm optimization (PSO) technique have attracted considerable attention among various modern heuristic optimization techniques. The GA has been popular in academia and the industry mainly because of its intuitiveness, ease of implementation, and the ability to effectively solve highly non-linear, mixed integer optimization problems that are typical of complex engineering systems. PSO technique is a relatively recent heuristic search method whose mechanics are inspired by the swarming or collaborative behavior of biological populations. Since the two approaches are supposed to find a solution to a given objective function but employ different strategies and computational effort, it is appropriate to compare their performance. This paper presents the application and performance comparison of PSO and GA optimization techniques, for flexible ac transmission system (FACTS)-based controller design. The design objective is to enhance the power system stability. The design problem of the FACTS-based controller 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 effort, computational time and convergence rate is compared. Further, the optimized controllers are tested on a weakly connected power system subjected to different disturbances over a wide range of loading conditions and parameter variations and their performance is compared with the conventional power system stabilizer (CPSS). The eigenvalue analysis and non-linear simulation results are presented and compared to show the effectiveness of both the techniques in designing a FACTS-based controller, to enhance power system stability.

A new single-pole switching technique for suppressing turbine-generator torsional vibrations and enhancing power stability and continuity

The author presents a new single-pole switching technique for reducing torsional torques in turbine blades and shafts and enhancing power system stability and transmission continuity. During the dead time between single-pole tripping and line reclosing, the significant negative-sequence current flowing into the nearby turbine-generator may cause supersynchronous resonance effect on low pressure turbine blades and even results in fatigue damage. Thus, during this time, the proposed grounding capacitor set up at the neutral of the wye transformer is inserted not only to eliminate this negative current but also to recover the prefault power transmission in advance. The induced adverse effect on turbine blades can be precluded. Adaptive reclosing is then applied to reclose the tripped phase and the grounding capacitor is switched off. This effectively improves the power system stability again and prevents further torque amplifications. This scheme is suitable for a single-circuit transmission line and can improve system reliability.

Decentralized adaptive backstepping control of electric power systems

In this paper, a decentralized adaptive backstepping excitation controller, tuned using a Particle Swarm Optimization technique (PSO), is designed for stability enhancement of multi-machine power systems. To achieve decentralization, each machine is modeled as an independent uncertain dynamic subsystem, where the uncertainty is a disturbance that represents the effects of the rest of the system on that particular machine. This disturbance is expressed as a polynomial function of electric power deviation, and its parameters are adapted using PSO. The proposed technique is illustrated with a two-area benchmark power system. This system exhibits inter-area oscillations which are effectively damped with the proposed decentralized controllers under severe contingencies, for which traditional power system stabilizers fail.

Modelling, simulation and optimal tuning of TCSC controller

A systematic procedure for modeling, simulation and optimal tuning the parameters of a Thyristor Controlled Series Compensator (TCSC) controller, for the power system stability enhancement is presented in this paper. For the simulation purpose, the model of singlemachine infinite bus (SMIB) power system with TCSC controller is developed in MATLAB/SIMULINK. The design problem of TCSC controller is formulated as an optimisation problem and genetic algorithm (GA) is employed to search for the optimal TCSC controller parameters. By minimizing a time-domain based objective function, in which the oscillatory rotor speed deviation of the generator is involved; stability performance of the power system is improved. The results obtained from simulations validate the effectiveness of proposed modelling and tuning approach for power system stability improvement. The simulation results also show that the proposed TCSC controller is effective in damping a range of small disturbance conditions in the power system. (Received in October 2006, accepted in February 2007. This paper was with the authors 1 month for 1 revision.)

ATC Enhancement Considering Transient Stability by Optimal Power Flow Control Using UPFC

With recent development of power electronics technology, power system stability enhancement and optimal power flow control by using Flexible AC Transmission System (FACTS) devices have so far been studied. The FACTS devices to relieve multiple constraints can also make it possible to enhance Available Transfer Capability (ATC) without construction of new transmission lines. In this paper, a new method for improving transient stability by Unified Power Flow Controller (UPFC) is proposed. Then the proposed method is applied to an OPF control method by using UPFC for relieving multiple constraints. The new OPF method is used for enhancement of ATC taking into account Transient stability constraints as well as overload and steady-state stability constraints. The OPF problem is formulated to minimize total capacity of inverters of UPFC. Effectiveness of the proposed method is shown by numerical examples for IEEJ East-10-machine test system.