Stability Of Multi-machine Power System Research Articles

Cuckoo Search Optimization Algorithm for Designing of a Multimachine Power System Stabilizer

In this paper, new metaheuristic technique cuckoo search optimization (CSO) is explored for an optimal and robust power system stabilizer (PSS) designing for multimachine power systems and performance is evaluated by comparing with well-established techniques, i.e., genetic algorithm (GA), particle swarm optimization (PSO), and new harmony search optimization (HSO). An eigenvalue-based multiobjective function is implemented for simultaneous control of damping factor and damping ratio to damp out low-frequency local and interarea modes of oscillations. The PSS parameters are so intended that unstable and/or lightly damped mode eigenvalues are shifted to a specified D-shape zone in the left half of the s-plane. The selected metaheuristic techniques GA, PSO, HSO, and CSO are used to obtain PSS parameters for 10-machines, 39-bus New England Power System and the controllers designed are named as GAPSS, PSOPSS, HSOPSS, and CSOPSS, respectively. The performance of all designed PSSs controllers is evaluated by eigenvalues analysis, nonlinear simulations, and performance indices for various operating conditions under different scenarios of severe disturbances and their comparative analysis is observed. The robustness of all designed PSSs controllers is observed by testing them on unseen operating conditions and results are compared for the same. The performance of CSOPSS is found to be better than other controllers designed.

Modified Particle Swarm Optimization Based on Lead-Lag Power System Stabilizer for Improve Stability in Multi-Machine Power System

Modified Particle Swarm Optimization Based on Lead-Lag Power System Stabilizer for Improve Stability in Multi-Machine Power System

Analytical Assessment for Transient Stability Under Stochastic Continuous Disturbances

With the growing integration of renewable power generation, plug-in electric vehicles, and other sources of uncertainty, increasing stochastic continuous disturbances are brought to power systems. The impact of stochastic continuous disturbances on power system transient stability attracts significant attention. To address this problem, this paper proposes an analytical assessment method for transient stability of multimachine power systems under stochastic continuous disturbances. In the proposed method, a probability measure of transient stability is presented and analytically solved by stochastic averaging. Compared with the conventional method (Monte Carlo simulation), the proposed method is many orders of magnitude faster, which makes it very attractive in practice when many plans for transient stability must be compared or when transient stability must be analyzed quickly. Also, it is found that the evolution of system energy over time is almost a simple diffusion process by the proposed method, which explains the impact mechanism of stochastic continuous disturbances on transient stability in theory.

A mathematical model of SOFC power plant for dynamic simulation of multi-machine power systems

Modern power networks are complex multi-component dynamic system with many operational levels made up of a wide range of renewable energy resources. The low frequency oscillations may undergo and sustain to cause system separation if adequate damping is not provided. This research work presents the mathematical model of Solid Oxide Fuel Cells (SOFC) within transmission network in order to dynamic stability analysis and control. The main contribution is to propose the new linearized Heffron-Philips model of the system under consideration the SOFC power plant to studying of low frequency oscillations. The eigenvalue-based objective function is used to search optimal multi-machine power system stabilizer (PSS) with the Particle Swarm Optimization (PSO) technique under various operating conditions. The effectiveness of the proposed model is tested on three-machine power system integrated with the single SOFC power plant. The time-domain simulation results are promising and illustrate the effectiveness of the proposed stabilizers. It can be damp the low frequency oscillations in the best possible procedure and significantly improves the stability performance of the case study system.

Design of Multi-Machine Power System Stabilizers with Forecast Uncertainties in Load/Generation

ABSTRACTOscillatory instability in modern power system has increased due to increasing complexity and integration of dynamic loads. Stability analysis of such interconnected power system is very prominent in the presence of uncertain load/generation. In this paper, a power system stabilizer (PSS) design approach, which aims at enhancing the oscillatory stability of the multi-machine power system over the specified uncertainty range in forecasted load/generation, is presented. With non-statistical uncertainty, problem of selecting design parameters of the PSS is formulated as an optimization problem with minimization of eigenvalues and damping ratios based multi-objective function. In order to account the non-statistical uncertainties, a boundary active power loss (BAPL) based objective function is proposed. This non-linear BAPL objective function is minimized for determining the optimal setting of the generators voltage and taps of the online tap changing transformers (OLTC) under various power system constraints. In this paper, both the objective functions are solved by a new metaheuristic technique known as gray wolf optimization (GWO). Boundary value-based approach is used to minimize the repeated load flows under uncertain load/generation scenarios. Improved small-signal stability (SSS) is achieved with optimal active power loss of uncertain power system. Eigenvalue and time domain analysis for New England system are carried out under wide range of disturbances to demonstrate the potential of the proposed approach.

On transient stability of multi-machine power systems through Takagi\u2013Sugeno fuzzy-based sliding mode control approach

The present research focuses on transient stability of multi-machine power systems in a full consideration regarding the performances of the Takagi–Sugeno fuzzy-based sliding mode control approach in association with the conventional sliding mode and also the optimal control approaches to improve the last finding outcomes in this area. Hereinafter, concerning the robustness of the sliding mode control approach toward parametric uncertainties and environment perturbations, in fact, a couple of different sliding mode control approaches are designed for mutual comparison, after a number of state-of-the-art technique considerations. To increase the control performance, the Takagi–Sugeno fuzzy-based approach is devised to provide the appropriate coefficients. Finally, the three control approaches are all carried out in the six-machine power system under the same condition and the investigated results are correspondingly provided to be analyzed. The results indicate that the proposed fuzzy-based control approach is well behaved with respect to other related ones.

An improved artificial bee colony algorithm for robust design of power system stabilizers

PurposeLow-frequency oscillations of 0.1 to 3 Hz are prejudicial to the power system stability. Within this context, this study aims to present an improved artificial bee colony (ABC)-based algorithm for optimal setting of multimachine power system stabilizers (PSSs) under several loading conditions simultaneously.Design/methodology/approachThe proposed approach symbolized by GCABC incorporates the grenade explosion technique and the Cauchy operator in the employed bee and onlooker bee phases to avoid random search. The parameters of the grenade explosion method and Cauchy operator based ABC(GCABC)-based PSSs (GCABC-PSSs) are tuned to place all undamped and lightly damped electromechanical modes in a prespecified zone in the s-plan.FindingsSimulation results based on eigenvalue analysis and nonlinear time-domain simulation show the potential and the dominance of the proposed controllers GCABC-PSSs in the improvement of the system stability under several disturbances and large set of operating points compared with the classical ABC method and genetic algorithm-based PSSs.Originality/valueThe novelty of the study is to efficiently implement a new optimization method called GCABC for an optimum design of PSSs. The design problem is formulated as a multi-objective optimization problem. In addition, all PSS parameters have been included in the space research.

Distributed Power Control for Transient Stability of Multimachine Power Systems

Transient stability is a key problem in power systems. Conventional methods enhancing the transient stability are always based on local information with a prior knowledge of an equilibrium point that may not be available for large disturbances. This paper puts forward a distributed power controller for improving transient stability of multimachine power systems. The distributed controller depends on the relative angular speed of each generator with respect to its neighboring generators, rather than on state errors from an equilibrium point, so that the requirement of knowledge of equilibrium point is relaxed. By making use of the Popov criterion, it is shown that the closed-loop system is asymptotically stable. Improvement of transient stability is then discussed. Simulation results compare the decentralized and distributed control for achieving frequency synchronization.

Performance of UPFC to enhance Power Stability in Multi-Machine Power System under Fault Condition

Performance of UPFC to enhance Power Stability in Multi-Machine Power System under Fault Condition

Distributed Stabilization of Multi-Machine Power Systems via Multi-Agent Flocking Control

In this paper, stabilization in terms of power swing reduction and angular frequency synchronism in multi-machine power systems is addressed by adopting the multi-agent flocking technique that is implemented through distributed static VAR compensators (SVC) as controllers. More precisely, power swing reduction and angular frequency synchronism in a multi-machine power system are re-formulated as stabilization on a related multi-agent state-space network. By inducing multi-agents collision under the suggested control algorithms, all the synchronous generators achieve angular frequency synchronism while power angles are specified to a same desired power angle. Numeric examples illustrate efficacy of the suggested technique.

Robust design of multimachine power system stabilizers based on improved non-dominated sorting genetic algorithms

Power system stabilizers (PSSs) associated with generators are mandatory requirements for damping low-frequency oscillations of a multimachine power system. Nevertheless, PSSs work well at particular network configuration and steady-state conditions for which they were designed. Therefore, the aim of this paper is the design of a robust PSS able to ensure the stability of the system for a wide range of loading conditions and various faults with higher performance. The main motivation for this design is to simultaneously shift as much as could be possible the lightly damped and undamped system electromechanical modes, at different loading conditions and system configurations, into pre-specified zone in the s-plane called D-shape sector. Hence, the problem of robustly tuning the PSSs parameters is formulated as a multiobjective optimization problem (MOP) with an eigenvalue-based objective functions. An improved version of non-dominated sorting genetic algorithms (NSGAII) is proposed to solve this MOP. The performance of the proposed NSGAII-based PSS (NSGAII-PSS) under different loading conditions, system configurations and disturbances is tested and examined for different multimachine power systems. Eigenvalue analysis and nonlinear simulations show the effectiveness and robustness of the proposed controllers NSGAII-PSSs and their ability to provide efficient damping of low-frequency oscillations.

Parameter Optimization of Multi-machine PSS Using Improved ABC Algorithms

For the parameter optimization of multi-machine Power System Stabilizer (PSS), a new method is proposed in this paper, which uses Improved Artificial Bee Colony (IABC) algorithm to coordinate the parameters of PSS. IABC aims to model the behavior of foragers of artificial bee colony more accurately and improve the performance of ABC algorithm in terms of local search ability. Simulation of IEEE four-machine two-area system verifies that, the PSS optimized by IABC has better performance than other algorithm in two typical modes.

Design of UPFC based Damping Controllerusing Neuro Fuzzy to Enhance Multi-machine Power System Stability

Objectives: Inter-area frequency oscillations are one of the major problems in the present power systems for smooth operation to transfer power from one area to another area through weak tie-lines. Methods/Statistical Analysis: If oscillations are not damped out quickly, problem like system instability, cascade failure and even blackouts may occur. Local mode of oscillations can be damped out by using Power System Stabilizers (PSS) but damping inter-area mode of oscillations using PSS may not be possible always. The major concerns in power system operation were damping power system oscillations. Flexible Alternating Current Transmission System(FACTS) technology has been used extensively for power control, voltage regulation, increasing the transient stability, and decreasing system oscillations. Among all FACTS devices, Unified Power Flow Controller (UPFC) ismost efficient which has the potential to increase the power flow and stability of the transmission line. Due the constantly changing nature of power system Conventional PI controller is not applicable. To overcome the drawback Artificial Intelligent(AI) techniques like Fuzzy Logic and Neural Network are combined as Neuro-Fuzzy based Controller. In this paper an Adaptive Neuro-Fuzzy Interface System(ANFIS) based UPFC is designedto enhance system stability. Findings: The main idea of FACTS technology is to improve controllability and optimizing the utilization of existing power system capacities using the high speed and reliable power electronic devices instead of mechanical controllers. FACTS controllers like UPFC provides set of interesting capabilities such as reactive power compensation, power flow control, voltage regulation, damping of oscillations. Thispaper has focused on the investigationofperformanceand the comparison ofUPFC on powerflowwithANFIS and Proportional Integral(PI) controllers.The comparative results of Eigen value and damping ratio with PI and ANFIS controllers have been shown. Thecomprehensive simulationcases areexaminedandtheresultsshows thattheproposedmodelare botheffectiveand reliable indampingtheinterareaoscillations oftwoareasystem. Applications/Improvements: The simulation studies are carried out in MATLAB/SIMULINK to analyze the performance and comparison of designed ANFIS and PI Controller. Keywords: Adaptive Neuro-Fuzzy Interface System(ANFIS), Proportional Integral (PI) Controller,System Stability, Inter-area Oscillation, Unified Power Flow Controller (UPFC)

An application of backtracking search algorithm in designing power system stabilizers for large multi-machine system

This paper deals with the backtracking search algorithm (BSA) optimization technique to solve the design problems of multi-machine power system stabilizers (PSSs) in large power system. Power system stability problem is formulated by an optimization problem using the LTI state space model of the power system. To conduct a comprehensive analysis, two test systems (2-AREA and 5-AREA) are considered to explain the variation of design performance with increase in system size. Additionally, two metaheuristic algorithms, namely bacterial foraging optimization algorithm (BFOA) and particle swarm optimization (PSO) are accounted to evaluate the overall design assessment. The obtained results show that BSA is superior to find consistent solution than BFOA and PSO regardless of system size. The damping performance that achieved from both test systems are sufficient to achieve fast system stability. System stability in linearized model is ensured in terms of eigenvalue shifting towards stability regions. On the other hand, damping performance in the non-linear model is evaluated in terms of overshoot and setting times. The obtained damping in both test systems are stable for BSA based design. However, BFOA and PSO based design perform worst in case of large power system. It is also found that the performance of BSA is not affected for large numbers of parameter optimization compared to PSO, and BFOA optimization techniques. This unique feature encourages recommending the developed backtracking search algorithm for PSS design of large multi-machine power system.

Non‐linear adaptive coordinated controller design for multimachine power systems to improve transient stability

Based on an adaptive backstepping approach, this study proposes a new coordinated control design where the coordination is done between the excitation controller of synchronous generators and steam-valve controller of turbine-governor systems in a multimachine power system by considering the critical parameters of both systems as unknown. This new coordinated control scheme can ensure the stability of multimachine power systems through the formulation of control Lyapunov functions (CLFs) and derive the adaptation laws to estimate the unknown parameters in the design process to prove the convergence of power systems using CLFs. The performances of the proposed control scheme are evaluated on a two-area four-machine 11-bus power system under different operating conditions such as three-phase short-circuit faults along with changes in loads. Simulation results are then compared with those of a similar controller where there is no coordination between the excitation and steam-valve controllers as well as with a coordinated sliding-mode controller. The results clearly show the effectiveness and superiority of the proposed control scheme.

Coordinated Switching Controllers for Transient Stability of Multi-Machine Power Systems

This paper proposes two switching controllers working in a coordinated manner to enhance the transient stability of multi-machine power systems. One is switching excitation controller (SEC) and the other is switching governor (SG). The SEC switches between a bang-bang excitation controller (BEC) and a conventional excitation controller (CEC) and the SG switches between a bang-bang governor (BG) and a conventional governor (CG), via a state-dependent switching strategy. The BEC and the BG are designed as bang-bang constant funnel controllers (BCFC), which are able to provide fast switching of excitation voltage and valve position between their upper and lower limits. A detailed steam turbine model including boiler pressure effect is considered in the controller design process. Simulation studies are undertaken in the IEEE 16-generator 68-bus power system to evaluate the control performance of the switching controllers, which include the cases that three-phase-to-ground fault and transmission line outage occur in the system, respectively. Coordination between the excitation loop and speed governing loop is studied. Two system resilience indexes are introduced, and the short-term resilience is investigated for the power systems with and without switching controllers installed, respectively.

Investigating the impacts of the SVCs and the SCs affecting to the transient stability in multi-machine power system

A new algorithm simulating the impacts of the VAR supporting devices such as the static var compensators (SVCs) and the synchronous condensers (SCs) under condition of symmetrical disturbances in multi-machine power system is mentioned. Some typical numerical examples are presented in this article.
 The comparisons of variation of the state parameters, such as the voltage, frequency, reactive power outputs and asynchronous torques…are simulated under condition of the action of the automatic voltage regulation systems of generators and of the VAR supporting devices.
 The transient energy margins are calculated and compared to assess the transient stability in multi-machine power system. Basing on this algorithm, the PC program uses the elements of the eigen-image matrix to bring the specific advantages for the simulation of the transient features of state variables.

Switching power system stabilizer and its coordination for enhancement of multi-machine power system stability

This paper proposes a coordinated switching power system stabilizer (SPSS) to enhance the stability of multimachine power systems. The SPSS switches between a bang-bang power system stabilizer (BPSS) and a conventional power system stabilizer (CPSS) based on a state-dependent switching strategy. The BPSS is designed as a bang-bang constant funnel controller (BCFC). It is able to provide fast damping of rotor speed oscillations in a bang-bang manner. The closed-loop stability of the power system controlled by the SPSSs and the CPSSs is analyzed. To verify the control performance of the SPSS, simulation studies are carried out in a 4-generator 11-bus power system and the IEEE 16-generator 68-bus power system. The damping ability of the SPSS is evaluated in aspects of small-signal oscillation damping and transient stability enhancement, respectively. Meanwhile, the coordination between different SPSSs and the coordination between the SPSS and the CPSS are investigated therein.

Decentralized multi-machine power system excitation control using continuous higher-order sliding mode technique

A new decentralized continuous higher-order sliding mode (HOSM) excitation control scheme is proposed to enhance transient stability and robustness of multi-machine power system. Power angle deviations are chosen as sliding variables. The HOSM control for uncertain nonlinear multi-machine power system is equivalently transformed into finite time stability problem of uncertain integrator chains. The alleged continuous HOSM excitation controller is composed of geometric homogeneous continuous control and super-twisting second-order sliding mode control law to achieve finite time convergence and overcome power system uncertainties. An adaptive gain, constructed for the super-twisting control item, enables reducing the switching control amplitude of excitation voltage to the minimum possible value along with a finite time convergence. The first-order and second-order time derivatives of power angles are estimated by the exact robust differentiators. Finite time stability of closed-loop power system is strictly proved. Simulation results for a three-machine system and 10-machine 39-bus New England power system demonstrate the effectiveness of the proposed decentralized continuous HOSM excitation control approach.

Improved Power System Stability Using Backtracking Search Algorithm for Coordination Design of PSS and TCSC Damping Controller

Power system oscillation is a serious threat to the stability of multimachine power systems. The coordinated control of power system stabilizers (PSS) and thyristor-controlled series compensation (TCSC) damping controllers is a commonly used technique to provide the required damping over different modes of growing oscillations. However, their coordinated design is a complex multimodal optimization problem that is very hard to solve using traditional tuning techniques. In addition, several limitations of traditionally used techniques prevent the optimum design of coordinated controllers. In this paper, an alternate technique for robust damping over oscillation is presented using backtracking search algorithm (BSA). A 5-area 16-machine benchmark power system is considered to evaluate the design efficiency. The complete design process is conducted in a linear time-invariant (LTI) model of a power system. It includes the design formulation into a multi-objective function from the system eigenvalues. Later on, nonlinear time-domain simulations are used to compare the damping performances for different local and inter-area modes of power system oscillations. The performance of the BSA technique is compared against that of the popular particle swarm optimization (PSO) for coordinated design efficiency. Damping performances using different design techniques are compared in term of settling time and overshoot of oscillations. The results obtained verify that the BSA-based design improves the system stability significantly. The stability of the multimachine power system is improved by up to 74.47% and 79.93% for an inter-area mode and a local mode of oscillation, respectively. Thus, the proposed technique for coordinated design has great potential to improve power system stability and to maintain its secure operation.