Stability Of Multi-machine Power System Research Articles

Robust coordinated control of damping controllers for improving of dynamic stability in multi-machine environment

In this paper, in order to improve the dynamic stability of multi-machine power system coordinated design of the unified power flow controller (UPFC) damping controller and power system stabiliser (PSS) is demonstrated. The coordinated design problem of PSS and UPFC damping controller over a wide range of loading conditions is converted to a constraint optimisation problem which is solved by a particle swarm optimisation (PSO) technique. The robustness of the coordinated stabilisers is warranted at wide range of operating conditions of power system. The effectiveness and robustness of the procedure are demonstrated through digital simulations on a four-machine power system embedding a UPFC and two PSSs. The performance of the coordinated stabilisers is presented through the non-linear simulation and some dynamic indices. The results of these studies illustrate that the proposed coordinated controllers have a distinguished capability in damping of inter-area oscillations and enhance greatly the dynamic stability of the power system.

Optimization of power system stabilizers using participation factor and genetic algorithm

This paper describes a method to determine the optimal location and the number of multi-machine power system stabilizers (PSSs) using participation factor (PF) and genetic algorithm (GA). The PF method is primarily used for number estimation and to identify the location of the PSSs, while the GA is applied to further reduce the number of PSSs, resulting in the optimization of their parameters and locations under different operating conditions. The problem is presented as a multi-objective optimization problem; maximizing the damping ratio of the electromechanical modes using different numbers of PSSs. The approach is successfully tested on the New England–New York interconnected system (16-machine and 68-bus), and its effectiveness in damping of local and inter-area modes of oscillations was proven. It is also compared to two other methods, which use only GA, in terms of damping ratio and computation time. In addition, the proposed approach demonstrates better performance compared to a fuzzy-based PSS when applied to the Iraqi National Super Grid System (INSGS).

A PSO Procedure for a Coordinated Tuning of Power System Stabilizers for Multiple Operating Conditions

The problem of coordinated tuning stabilizers in multi-machine power systems is formulated here as a sequence ofoptimization problems. The design problem of stabilizers is converted to a nonlinear optimization problem with a multiobjectivefitness function. The proposed method employs particle swarm optimization (PSO), an algorithm to searchfor optimal parameter settings of a widely used conventional fixed-structure lead-lag power system stabilizers(CPSSs). One of the main advantages of the proposed approach is its robustness to the initial parameter settings. Inaddition, the quality of the optimal solution does not rely on the initial guess. The robustness and performance of thenewly designed controllers is evaluated in a large sixteen-machine power system subjected to different loadingconditions in comparison with the genetic algorithm (GA) based PSSs design. The superiority of the controllerdesigned is demonstrated through the nonlinear time-domain simulation and some performance indices studies. Theresults analysis reveals that the tuned PSSs with proposed objective function has an excellent capability in dampingpower system low-frequency oscillations.

A simplified nonlinear controller for transient stability enhancement of multimachine power systems using SSSC device

In this paper, a simplified nonlinear method is proposed to enhance the transient stability of multimachine power system by using a Static Synchronous Series Compensator (SSSC). The rate of dissipation of transient energy is used to determine the additional damping provided by a SSSC. The proposed algorithm is based on the direct Lyapunov method. The simplicity of the proposed scheme and its robustness with respect to large disturbances constitute the main positive features. Simulation results in the case of 3-machines power system show the effectiveness of the proposed method under large disturbances (3-phase and single phase short-circuits).

Adaptive Fuzzy Sliding Mode Power System Stabilizer Using Nussbaum Gain

Power system stability is enhanced through a novel stabilizer developed around an adaptive fuzzy sliding mode approach which applies the Nussbaum gain to a nonlinear model of a single-machine infinite-bus (SMIB) and multi-machine power system stabilizer subjected to a three phase fault. The Nussbaum gain is used to avoid the positive sign constraint and the problem of controllability of the system. A comparative simulation study is presented to evaluate the achieved performance.

A new optimization approach for multi-machine power system stabilizer design using a smart bacteria foraging algorithm

This paper presents a new optimization method for designing the parameters of a power system stabilizer (PSS) using a smart bacteria foraging algorithm (SBFA). The proposed technique, which is a modification of the bacteria foraging method (BFA), can direct bacteria by performing a tumble with a smart unit of length, decreasing the cost function better than the conventional BFA method. This algorithm not only considers social intelligence, but also emphasizes the individual intelligence of bacteria for finding a better nutritional path. A new cost function in the proposed SBFA has been used for specifying the direction of movement after a tumble. This approach led to a higher convergence speed and also better performance than the BFA. The effectiveness of the proposed method has been tested on a multi-machine power system while considering a frequency error-based objective function to enhance damping of the electromechanical oscillation modes. Simulation results for the proposed method are compared with conventional PSS, BFA- and fuzzy-based PSS methods. The results show the superior performance of the proposed SBFA-based PSS in comparison with other techniques for damping power system oscillations.

A sensitivity based approach to assess the impacts of integration of variable speed wind farms on the transient stability of power systems

The impact of large penetration of wind power on the transient stability of multi-machine power systems is discussed in this paper. Variable speed wind farms with doubly fed induction generators (DFIG) are considered. A new index based on the sensitivity of the DFIG terminal voltage is used to assess the transient stability margin of power systems, both for constant wind speed condition and during a sudden change in wind speed. Suitable locations for connecting the DFIG to an existing power system are identified with the help of this index. The effect of increase in wind power penetration on the transient stability condition of the existing power system is studied. The proposed index is also used to select the optimum crowbar resistance during fault ride-through operation.

Stability Enhancement of a Multimachine System Using STATCOM with Supplementary Controller

This paper investigates the improvement in the stability of a multi-machine power system using Static Synchronous Compensator (STATCOM). A systematic procedure for modelling, simulation and optimal tuning of the parameters of a STATCOM controller for stability enhancement is presented. The design of the proposed supplementary controller is formulated as an optimization problem, and adopts the particle swarm optimisation (PSO) algorithm for the optimal tuning of the controller parameters. The performance of the proposed controller is tested in a multimachine power system and results are compared with and without controller. Simulation results under different operating conditions are presented to highlight the effectiveness of the proposed controller

Robust design of multimachine power system stabilizers using fuzzy gravitational search algorithm

This paper presents a novel Fuzzy Gravitational Search Algorithm (FGSA) for optimal design of multimachine power system stabilizers (PSSs). The FGSA technique is characterized as simple, robust and capable to solve difficult combinatorial optimization problems. For achieving optimal tuning of PSS parameters, the problem is formulated as an optimization problem with the time domain-based objective function over a wide range of operating conditions and is solved by the proposed FGSA technique. The performance of the proposed FGSA based-PSS design is validated for two multimachine systems: a 3-machine 9-bus system and a 10-machine 39-bus. The effectiveness and robustness of proposed method is demonstrated using many performance indices. The results prove that the proposed FGSA assures a well damping to the electromechanical modes of oscillations for a wide range of system operation conditions. The superiority of the proposed method is proved compared to different optimization methods.

Design of decentralized robust controller for voltage regulation and stabilization of multimachine power systems

This paper presents a decentralized state-feedback controller design based on robust control theory to ensure system stability and voltage regulation in multimachine power systems. The power system is decomposed in n subsystems each represented by a state-space model with bounded parameter uncertainties and unknown input disturbances of class L∞ which model couplings with the generators of the others subsystems. The proposed controller designed according to a Riccati-based approach is robust with respect to uncertain network parameters and counteracts the effects of the disturbances. A stability analysis in presence of L∞ disturbances is also given. The control law is straightforward and cost effective because it is function of constant gains and of local measurable machine variables. Numerical simulations give evidence of the achievements in terms of system transient stability as well as voltage regulation, also in comparison with another design technique.

Improving Transient Stability of a Multi-Machine Power Network Using FACTS Devices and Nonlinear Controller Tuned by PSO

Transient stability is one of the main issues in the field of power systems. On the other hand, using FACTS devices has been proposed for the purpose of maximizing the lines conductivity given the restrictions involved, including the issue of stability. This study seeks to take steps towards the improvement of a multi-machine power system stability in faulty conditions, using two FACTS devices including TCSC and SVC. The control system for the FACTS devices is constructed here based on the so called energy function method. Meanwhile, in order to achieve a prescribed optimal performance, the coefficients of the designed controller are tuned by PSO algorithm. Possessing the theoretical analysis, the simulation results are also demonstrated to show the performance of the proposed control algorithm.

Lyapunov-Based Decentralized Excitation Control for Global Asymptotic Stability and Voltage Regulation of Multi-Machine Power Systems

This paper proposes a novel Lyapunov-based excitation control (LEC) technique to deal with both global asymptotic stability and voltage regulation for the multi-machine power systems. Lyapunov function is built as a quadratic form of the control objectives consisted of active power offset, rotor speed offset and terminal voltage offset. A completely controllable linear system is constructed to design the trajectories of the time-derivatives of the control objectives. Furthermore, time-derivative of Lyapunov function (TLF) is also expressed as a quadratic form of the control objectives. Feedback gains are chosen to guarantee the negative definition of the TLF for any real number except for the equilibrium point. Therefore, the global asymptotic stability is achieved. The design flexibility of the proposed method provides convenience to introduce the voltage feedback signal for maintaining acceptable voltage level. The system voltage is forced to converge to its reference accompanying with the energy attenuation of Lyapunov function. As a result, voltage deviation is eliminated when Lyapunov function is equal to zero. Finally, a Lyapunov-based decentralized excitation controller is developed for the multi-machine power systems, and it is only related to local measurements. Simulations on a six-machine power system have illustrated better performances in comparison to the existing controllers.

Dynamic genetic algorithms for robust design of multimachine power system stabilizers

Genetic Algorithms (GAs) are the most popular used methods of the evolutionary algorithm family. GA effectiveness highly depends on the choice of the search space range for each parameter to be optimized. The search space being a set of potential solutions may contain the global optimum and/or other local optimums. Being often a problem-based experience, a bad choice of search spaces will result in poor solutions. In this paper, a novel optimization approach based on GAs is proposed. It consists in moving the search space range during the optimization process toward promising areas that may contain the global optimum. This dynamic search space allows the GA to diversify its population with new solutions that are not available with fixed search space. As a result, the GA optimization performance can be improved in terms of solution quality and convergence rate. The proposed approach is applied to optimal design of multimachine power system stabilizers. A 16-machine, 68-bus power system is considered. The obtained results are evaluated and compared with other results obtained by ordinary GAs. Eigenvalue analysis and nonlinear system simulations demonstrate the effectiveness of the proposed approach in damping the electromechanical oscillations and enhancing the system dynamic stability.

Power System Stabilizer and Secondary Voltage Regulator Tuning for Multi-machine Power Systems

This article aims to present the performance of a B-spline neural network scheme for tuning both the reactive power provision controller from synchronous machines and power system stabilizers in multi-machine power systems. The B-spline neural network is an efficient tool to implement the adaptive control voltage and power system stabilizer coordination, with the possibility of carrying out this task on-line, taking into account the systems' non-linearities. One of the main tasks within this context is to estimate the best power system stabilizer's parameters and adjust the proportional-integral parameters for reactive power provision. In this article, this is solved by a neural network algorithm. The applicability of the proposal is demonstrated by simulation on two test systems. Results show that the proposed coordination scheme is comparable to that obtained by a conventional design, without requiring a strict model analysis.

A new-fangled adaptive mutation breeder genetic optimization of global multi-machine power system stabilizer

This paper presents the design and implementation of Power System Stabilizers in a multimachine power system based on innovative evolutionary algorithm overtly as Breeder Genetic Algorithm with Adaptive Mutation. For the analysis purpose a Conventional Power System Stabilizer was also designed and implemented in the same system. Simulation results on multimachine systems subjected to small perturbation and three phase fault radiates the effectiveness and robustness of the proposed Power System Stabilizers over a wide range of operating conditions and system configurations. The results have shown that Adaptive Mutation Breeder Genetic Algorithms are well suited for optimal tuning of Power System Stabilizers and they work better than conventional Genetic Algorithm, since they have been designed to work on continuous domain. This proposed Power System Stabilizer is demonstrated through a weakly connected three multi-machine test systems.

Multi-machine power system stabilizer design by using cultural algorithms

Conventional power system stabilizer (CPSS) has been widely used as a supplementary controller to damp out the low frequency oscillations. The tuning of CPSS parameters for nonlinear power systems in a robust way in order that the overall system stability can be improved is a major drawback of CPSS. Several meta-heuristic optimization techniques have been tried out to overcome this shortcoming. This paper presents a new technique named cultural algorithms (CAs) to tune the PSS parameters. This technique is robust and computationally efficient as compared with other meta-heuristic algorithms. Simulations are carried out on two typical multi-machine electric power systems. The results clearly verify that the proposed method improves the dynamic stability of the system, especially when the operating point changes.

Application of Lyapunov Theory and Fuzzy Logic to Control Shunt FACTS Devices for Enhancing Transient Stability in Multimachine System

This paper proposes the control strategy of the shunt Flexible AC Transmission System (FACTS) devices to improve transient stability in multimachine power system. The multimachine power system has high nonlinear response after severe disturbance. The concept of Lyapunov energy function is applied to derive nonlinear control strategy and it was found that the time derivative of line voltage is not only can apply to control the shunt FACTS devices in multimachine system but also is locally measurable signal. The fuzzy logic control is also applied to overcome the uncertainty of various disturbances in multimachine power system. This paper presents the method of investigating the effect of the shunt FACTS devices on transient stability improvement. The proposed control strategy and the method of simulation are tested on the new England power system. It was found that the shunt FACTS devices based on the proposed nonlinear control strategy can improve transient stability of multimachine power system.

Nonlinear Koopman Modes and a Precursor to Power System Swing Instabilities

We suggest a precursor to phenomena of loss of transient stability in multi-machine power systems. This precursor is based on discovery of [Y. Susuki, I. Mezic , and T. Hikihara, J. Nonlinear Sci., vol. 21, no. 3, pp. 403-439, June 2011], an emergent transmission path of energy from many oscillatory modes to one oscillatory mode that represents an instability phenomenon of interest. The pathway from high frequency modes to the lowest frequency mode is called the coherent swing instability (CSI). The modes are extracted from sensor data or data provided by simulation outputs of power system oscillations by using the Koopman mode analysis that is based on a fully nonlinear spectral theory and represents an extension of linear oscillatory mode analysis. The CSI transmission path is identified by computation of the so-called action transfer operator that is derived by refining a mathematical model of transient stability using the Koopman mode analysis. This provides a new technique for monitoring the loss of transient stability by a combination of practical data, mathematical modeling, and computation.

Multi-machine power system stabilizer design using improved particle swarm optimization (PSO) with time-varying acceleration coefficients

An efficient and most famous tool to enhance damping of the power system low frequency oscillations is the conventional widely used lead-lag Power System Stabilizer (PSS). To achieve the desired level of robust performance under transient situation, selecting a suitable design method for optimal tuning of PSS parameters is very important in multi-machine power system. Because, it is a multimodal and difficult combinatorial optimization problem, this paper presents a novel parameter automation strategy for Particle Swarm Optimization (PSO) called PSO with Time-Varying Acceleration Coefficients (PSO-TVAC). This optimization method has a strong ability to successfully control both global and local search in each iteration process for considerably increasing the probability of finding the global optimum solution. The PSO-TVAC algorithm is applied to optimal tuning PSS parameters problem in order to reduce the PSS design effort and find the best possible solution within a reasonable computation time. For this reason, the robustly selection of PSSs parameters is converted as an optimization problem based on the time domain-based objective function under different operating conditions. The robustness of the proposed method is demonstrated on a multi-machine power system in comparison with the classical PSO and conventional method based designed PSSs. It is shown through the nonlinear time domain simulation and some performance indices for a wide range of loading condition. The analysis of the results shows that the improved PSO-TVAC is not only very effective but also provides an excellent ability for damping low frequency oscillations and greatly enhance the dynamic stability of the power system. Moreover, the proposed PSO-TVAC algorithm is superior than that of the classical PSO one in terms of accuracy, convergence and computational effort. Key words: Power system stabilizer (PSS) design, particle swarm optimization, power system dynamics, time-varying acceleration coefficients.

A new robust adaptive fuzzy sliding mode power system stabilizer

This paper presents a novel power system stabilizer based on adaptive fuzzy sliding mode approach without reaching phase. We consider consequences of a major post disturbance on a power system for three different loading and operating conditions. Speed deviation and accelerating power are selected as controller inputs. A new sliding surface enabling for sliding to occur at any state initial conditions is used to develop a robust controller. Moreover, two adaptive fuzzy systems are used to approximate power system dynamics. Stability issue is addressed via Lyapunov synthesis. The robustness of the proposed method is verified on a single-machine infinite-bus and on a multi-machine power system stabilizer under different operating conditions. A comparative simulation study is presented to evaluate achieved performance enhancements showing better oscillations damping and faster transient dynamic behaviour over three considered controllers: a conventional, a dual-input and a classical sliding mode power system stabilizer.