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This paper deals with the application of Thyristor Controlled Series Reactor (TCSR) FACTS controller for mitigation of congestion in one or more lines of a power system. When generation is close to thermal limit then one or more healthy lines may face congestion, if some line is out of operation due to fault or maintenance. For a given voltage difference between two end buses of a congested line, the line current can be reduced to normal value or congestion can be mitigated by increasing the reactance of that line. The reactance of the line can be suitably increased with the help of series TCSR FACTS Controller. The reactance of the Controller can be suitably increased by firing the SCRs at the appropriate firing angles. TCSR FACTS Controller has been implemented to mitigate the congestion in IEEE 5-Bus and Modified IEEE 14-Bus Test systems. The TCSR FACTS Controller is successful in mitigation of congestion of any level.

The increasing number of low-frequency oscillation events has posed significant challenges to power system stability. It is imperative to accurately identify and properly control generators with poor or negative damping contribution for better oscillation damping. This paper proposes a hybrid energy and mode decomposition-based method for evaluating generators damping in multi-machine power systems. It is derived that the aggregate electric torque can be modeled as the superposition of electric torques in different modes. In each oscillation mode, the electric torque can be decomposed into the damping torque and the synchronizing torque. Moreover, a novel oscillation energy function is developed to evaluate generators’ damping effect in each oscillation mode. The result proves that in each oscillation mode, generators with attenuated oscillation energies have negative damping effects. Simulation results in single and multinegative damping generators cases, as well as the comparison with other methods, demonstrate the effectiveness and robustness of the proposed method for damping evaluation.

A composite learning dynamic surface control is proposed for a class of multi-machine power systems with uncertainties and external disturbances by using fuzzy logic systems (FLSs) and disturbance observer (DOB). The main characteristics of the proposed strategy are as follows: (1) The approximation ability of FLSs for nonlinear model of multi-machine power systems is enhanced considerably by using the composite learning method and providing additional correction information for the FLSs. These findings differ considerably from previous designs that focus directly on the system's tracking performance. (2) The filtering errors caused by the utilizations of the first-order low-pass filters in dynamic surface control (DSC) are compensated effectively by designing the compensating signals in the control law design process. (3) The compound disturbances including the FLSs' approximation error and external disturbances are estimated and mitigated by constructing DOB. Finally, the proposed control algorithm is verified on the StarSim Hardware-in-loop experimental platform, and the experimental results validate the effectiveness of the proposed control strategy in suppressing disturbances and enhancing the robustness of the controller.

This paper proposes a new controller for stability and voltage improvement of power networks equipped by wind turbine which optimize the dynamical response of power systems performances (voltage and transient stability) after fault. The proposed control algorithm based on new Adaptive Neuro-Fuzzy Inference System (ANFIS) controller to enhance the mechanical power of the synchronous machine into power system. The efficiency of developed control strategy has been tested using IEEE 9 Bus. Simulation results have showed that the proposed method perform better performances over wide range of disturbances for three considered scenarios studied.

This paper proposes a novel nonlinear decentralized control method for a class of multi‐machine power systems. The aim is to construct a suitable decentralized feedback control law so as t...

This paper describes an application of nonlinear adaptive Hamilton minimax control to multi-machine power systems with steam valve controllers. The controllers are designed explicitly to maintain transient stability of systems. First, the feedback link is introduced to transform the traditional power system model into Hamilton structure. It is worth mentioning that in the process of building the system model and designing the controllers, this paper considers the problem of interconnection interference. The proposed controllers enable the system to have L2 interference suppression characteristics in the case of maximum disturbance. Finally, the simulation results show that the adaptive Hamilton minimax method has better transient performance.

Turbine generator shaft torsional oscillations is an interdisciplinary power system dynamic problem as it involves mechanical and electrical engineering. Torsional oscillations occur in the mechanical for electrical reasons. Torsional oscillations cause fatigue life expenditure of the mechanical shaft system. There have been great motivations to mitigate the shaft torsional oscillations especially when unrestricted high speed reclosure (HSR) is utilized on the overhead transmission lines emanating from a generation station. Mitigation of torsional oscillation compromises between the use of HSR and preserving the mechanical integrity of the involved turbine generator set. Therefore, braking resistor (BR) controlled by fuzzy logic controller is presented in this paper as a low cost, reliable mean for torsional oscillations mitigation. BR was first utilized for the system transient stability enhancement. It serves as an extra load capable of dissipating extra generated power in case of system severe faults close to a generation station consequently prevents generator pole slipping conditions. IEEE 3 machine 9 bus system is adopted in this paper to test the effects of BR on shaft torsional oscillations mitigation in interconnected power system. Comparative simulation studies between the unsuccessful reclosure with and without fuzzy controlled BR prove the effectiveness of the scheme for mitigation of torsional oscillations significantly.

The paper studies the robust control for multi-machine power systems under parametric uncertainties, perturbed mechanical input power and unknown variable communication time-delay. Only relative speed of each electrical generator is available for measurement. The theoretical investigations show that the proposed algorithm synchronizes the multi-machine power system with the required accuracy in the normal mode and under symmetrical 3-phase short circuit faults which occur on ransmission lines. Numerical investigations illustrate the efficiency of the proposed scheme for the three machines and the New England Power system benchmark.

Manifold consensus in the multi-objective sense of frequency synchronism, torque angle specification, power swing reduction, and inter-generator dynamics decoupling in multi-machine power systems i...

This paper introduces a new robust controller with cascaded fuzzy blocks as a power system stabilizer (CFPSS) to enhance damping during low-frequency oscillations. This CFPSS is designed to act as a nonlinear lead–lag PSS with a given number of compensation blocks. To demonstrate the efficiency and the robustness of this proposed stabilizer, simulation results performed on the IEEE three-generator nine-bus multi-machine power system subjected to a three-phase short-circuit fault have been carried out. The parameters of the proposed PSS and those of the conventional IEEE linear lead–lag PSS have been tuned by a recently developed optimization technique (krill herd algorithm). The robustness of this novel CFPSS is proved, by optimizing the parameters of the two PSSs for one operating point (normally loaded system) and applying them to other operating points (case of heavy and low loads) with some key parameters variation. The obtained results have shown the superiority and the robustness of the CFPSS comparatively to the conventional IEEE lead–lag PSS in terms of oscillations damping over a wide range of operating conditions and against parametric variation. The same conclusions have been drawn in the case of a large power system (IEEE 16-machine, 68-bus test system) characterized by its local and inter-area oscillations modes.

The role of Power System Stabilizer (PSS) in the power system is to provide necessary damping torque to the system in order to suppress the oscillations caused by a variety of disturbances that occur frequently and maintain the stability of the system. In this paper, a PSS design technique is proposed using Whale Optimization Algorithm (WOA) by considering eigenvalue objective function. Two bench mark multi machine test systems: three- generator nine- bus system, two- area four- generator inter connected system working on various operating conditions are considered as case studies and tested with the proposed technique. Extensive simulation results are obtained and effectiveness of proposed WOA-PSS are compared with well - known PSO and DE based stabilizers under several disturbances.

In this paper, a novel energy flow analysis (EFA) is proposed based on the signal reconstruction and decomposition to investigate the electromechanical oscillations. In contrast to the conventional EFA, the connection between the proposed EFA and modal analysis (MA) can be quantitatively revealed for arbitrary models of synchronous generators in multi-machine power systems. Firstly, the time-domain implementation (TDI) of the proposed EFA is designed. Specifically, the measurements at the terminal of a local generator are reconstructed through an exponential operator and then decomposed with respect to an angular frequency. Then, the mode-screened damping torque coefficient is defined to extract the damping feature with respect to an electromechanical oscillation mode. After that, the frequency-domain implementation (FDI) is derived. Specifically, the Parsevals Theorem is applied to transform the proposed EFA from the time domain to frequency domain. On this basis, the consistency between the proposed EFA and MA is strictly proved, which is applicable for arbitrary models of synchronous generators in multi-machine power systems. Additionally, the application procedure of the proposed EFA in investigating electromechanical oscillations is given. Finally, the proposed EFA is substantially demonstrated in multiple case studies.

Design of power system stabilizer (PSS) withstanding critical situations is a challenging task. In this paper, an effective method for the design of a coordinated multiple PSS in power systems are offered and weaknesses of the existing methods are disclosed. The setup includes the nonlinear model of the system, a specific multi-objective function and a newly developed meta-heuristic Hyper-Spherical Search (HSS) optimization algorithm. The objective function includes both eigenvalue stability index (SI) and nonlinearity index (NI). The employed new NI is the second order modal interaction of the lightly damped electromechanical modes. The performance of the proposed Stability-Nonlinearity index (SN) based PSS design by HSS (SNPSS-HSS) is compared with SNPSS-GA, SI based PSS (SPSS) and the conventional design method (CPSS) under various operating conditions and disturbances. The investigations are conducted over both a single lead PSS and PSS2B. The performance is detailed using time domain simulations, SI and NI analysis. A four-machine two-area system and the IEEE 39-bus system are utilized for test purpose. The results of extensive simulations indicate the superiority of SNPSS-HSS design with respect to the others. The obtained relative stability is higher and the nonlinearity index is lower than the product of the other designs. Besides, as it is expected, using a high degree of freedom PSS2B improves the performance of the aforementioned algorithms.

In this paper, a neural decentralized adaptive quantized dynamic surface control scheme is proposed for a class of large-scale multi-machine power systems with static var compensator (SVC) and unknown line-transmission time delays. The main contributions of the proposed method are summarized as follows: 1) a decentralized dynamic surface quantized control scheme with simple structure is proposed for the large-scale multi-machine systems with SVC, where the “explosion of complexity” problem in backstepping method and the complexities introduced by SVC are overcome; 2) the unknown line-transmission time delays between different generators are considered and dealt with by introducing the finite-cover lemma with radial basis function neural networks (RBFNNs) approximator, which leads to the arbitrarily small $\mathcal {L}_{\infty }$ a tracking performance; 3) the strong nonlinearities, uncertain parameters and external disturbances of the system are considered and the number of the estimated parameters is greatly reduced by estimating the weight vector norm of neural networks instead of estimating the weighted vector itself. It is proved that all the signals in the control system are ultimately uniformly bounded b and can be made arbitrarily small. Simulation results show the validity of the proposed method. a Here, the $\mathcal {L}_{\infty }$ norm is defined as $\left \Vert{ x}\right \Vert _{\infty }\mathop{=}\limits^{\Delta } \sup \limits_{t\geq 0}\left \vert{ x(t)}\right \vert $ and we say $x\in \mathcal {L}_{\infty }$ when $\left \Vert{ x}\right \Vert _{\infty }$ exists. b Here, we say $x(t)$ is ultimately uniformly bounded if there exist positive constants $b$ and $c$ , independent of $t_{0}\geq 0$ , and for every $a\in (0,c)$ , there is $T=T(a,b)$ , independent of $t_{0}$ , such that $\left \Vert{ x(t_{0})}\right \Vert \leq a\Rightarrow \left \Vert{ x(t)}\right \Vert \leq b$ , $\forall t\geq t_{0}+T$ .

The conception of electromechanical oscillations initiates in the power network when there is an installation of the generator in parallel with the existent one. Further, the interconnection of multiple areas, extension in transmission, capricious load characteristics, etc. causes low-frequency oscillations in the consolidated power network. This paper proposes variants of a booming population-based grey wolf optimization (GWO) algorithm in the tuning of power system stabilizer parameters of a multi-machine system in damping low-frequency oscillations. The parameters have been tuned by framing an objective function considering the improving damping ratios for the system states with lesser damping ratios and shifting the system eigenvalues towards the left-hand side of s-plane for the improved settling characteristics for the oscillations in the system. The requisites of stabilizer strategy are mapped with the hallmarks of prevalent algorithms and designed hybrid versions of GWO for the enhancement of the multi-machine power system stability. Four variants of GWO technique are nominated based on the competent stabilizer performance namely, modified grey wolf optimization (MGWO), hybrid MGWO particle swarm optimization (MGWOPSO), hybrid MGWO sine cosine algorithm (MGWOSCA) and hybrid MGWO crow search algorithm (MGWOCSA) for the designed multi-machine power network. The proposed methods have been realized with the statistical analysis on the 23 benchmark functions. Nonparametric statistical tests, namely, Feidman test, Anova test and Quade tests, have been performed on the test system, further analysed in detail. A detailed comparative analysis under the self-clearing fault is presented to illustrate the suitability of the proposed techniques. For the analysis purpose, the location of system eigenvalues has been observed along with their oscillating frequencies and corresponding damping ratios. Further, the damping nature offered with considered system uncertainty for the system states also presented with the PSS parameters obtained by the proposed algorithms.

The system frequency response (SFR) model describes the average network frequency response after a disturbance and has been applied to a wide variety of dynamic studies. However, the traditional literature does not provide a generic, analytical method for obtaining the SFR model parameters when the system contains multiple generators; instead, a numerical simulation-based approach or the operators’ experience are the common practice to obtain an aggregated model. In this paper, an analytical method is proposed for aggregating the multi-machine SFR model into a single-machine model. The verification study indicates that the proposed aggregated SFR model can accurately represent the multi-machine SFR model. Furthermore, the detailed system simulation illustrates that the SFR model can also accurately represent the average frequency response of large systems for power system dynamic studies. Finally, three applications of the proposed method are explored, with system frequency control, frequency stability, and dynamic model reduction. The results show the method is promising with broad potential applications.

This paper derives the initial value calculation of a multi-machine power system with a detailed sixth-order model of synchronous generator equipped with exciter and turbine systems. The method is generalized that can be used for any model including the reduced model of synchronous generators such as two-axes, one-axis, and classical model. A Matlab-based package was developed for calculating the initial values and simulating a multi-machine power system. The test system used in the study is IEEE 16-machine 68-bus system.

In this study, a methodology for partial eigenstructure assignment (PEVA) is applied to dampen electromechanical oscillations in electrical multi-machine power systems. The approach is anchored in allocating a small number of undesirable eigenvalues, for example, which are poorly damped, preserving the other eigenvalues in the system - the so-called no-spillover spectrum. The new position of the selected eigenvalues is carried out based on the partial controllability analysis of the system, in order to minimize the control effort. Simulation examples using a system with 68 buses, 16 generators and five areas showed that the presented methodology is efficient in dampening the local and inter-area oscillation modes when compared to the classic power system stabilizers (PSS). The quality of the solution is illustrated through computer simulations, eigenvalues tables and mode-shapes.

Most of large scale systems are described by their complex mathematical model’s structures which caused by the overlapping between its inputs and outputs variables. In many cases, the complexity of the model may lead to lose some part of the input-output signals. Besides, it obscures study and analysis of such type of systems for researchers. Many studies have been discussed the design of simpler controller based on the mathematical structure of the systems’ model, wherein the aim was to decrease control complexity. The main objective of this manuscript is to benefit from the multi-overlapping structure of complex systems in order to design a simpler controller using loop approach; the latter allows highlighting the advantages of applying the overlapping decomposition strategy in order to improve the robustness of the designed controller. Therefore, it can be considered as an efficient strategy suitable for such type of large scale systems. A multi-machine power system with loop structure is considered in order to demonstrate the usefulness of the proposed design.

The multimachine system is one of the most common systems present in the power system network. System expansion is necessary due to ever-increasing load, and thus, the analysis of the response of multimachine becomes important too. UPFC is the most common FACTS device used in power system in current scenario as it can control all parameters of the power at same time. IEEE 14 bus test system with three generators has been taken for the analysis, and also voltage stability is calculated with the help of different indices to find out suitable position of UPFC to be implemented in the system. All the simulation is carried out in the PSAT software [1]. The loss with and without UPFC is calculated.

A modified flux-coupling type superconducting fault current limiter (SFCL) is proposed here for suppressing fault currents. The modified SFCL consists of a coupling transformer, an yttrium barium copper oxide (YBCO) pancake coil, and a controlled switch. By flexibly adjusting the controlled switch's contact states based on the system operational conditions, the coupling transformer's primary inductance as well as the YBCO coil's normal-state resistance are incorporated into the main system for current limitation. Because the modified SFCL has the advantages of resistive and inductive SFCLs, it may improve the power system's transient behavior. Hence, the SFCL's effect on the transient stability of a multi-machine power system was also theoretically investigated. Further, simulations were conducted for accessing the SFCL's performance characteristics under different fault conditions. The results show that using the proposed SFCL can effectively restrain the increased fault current and improve the bus voltage sag; meanwhile, the imitated multi-machine system's power-angle oscillation can be obviously reduced.

This paper proposes a method to design power system stabilizers (PSSs) based on single-machine infinite-bus system models to mitigate the risk of low-frequency electro- mechanical power oscillations in an N-machine power system. First, models of N fabricated identical-machine power systems are established for the N-machine power system. Analysis in the paper indicates that the electromechanical oscillation mode of fabricated identical-machine power systems with the least damping is of less damping than the electromechanical oscillation modes of N-machine power system. Second, it is proved that models of fabricated identical-machine power systems are dynamically equivalent to the single-machine infinite-bus system models. Finally, it is suggested that the PSSs are designed using single-machine infinite-bus system models to enhance the least damped electromechanical oscillation mode of fabricated identical-machine power systems. This eventually improves the damping of electromechanical oscillation modes of N-machine power system, thus mitigating the risk of low-frequency electromechanical power oscillations. In the paper, the proposed method is demonstrated and evaluated by using three well-known example multi-machine power systems. Effectiveness of PSSs is confirmed by the results of modal computation and simulation.

Design of a new method for a robust, nonlinear and intelligent stabilizer based on fuzzy logic combining a conventional controller, lead-lag power system stabilizer (PSS), is suggested in this paper for single- and multi-machine power systems. The proposed strategy takes into account the stability of the system by damping the oscillations separately of the operating point and this even for several operating conditions. Simulation of two power systems Kundur made it possible to determine the performance of the proposed fuzzy logic power system stabilizer (FPSS) versus the various quotas commonly encountered in the network. The implementation of the proposed FPSS is examined for trapezoidal, Gaussian and triangular membership functions and compared to the conventional PSS. Increasing of speed deviation and acceleration are taken like inputs. To show the efficacy of the proposed FPSS, the simulation results of the framework are implemented in MATLAB/Simulink.

With the penetration of renewable generation, electric vehicles and other random factors in power systems, the stochastic disturbances are increasing significantly, which are necessary to be handled for guarantying the security of systems. A novel stochastic optimal control strategy is proposed in this paper to reduce the impact of such stochastic continuous disturbances on power systems. The proposed method is effective in solving the problems caused by the stochastic continuous disturbances and has two significant advantages. First, a simplified and effective solution is proposed to analyze the system influenced by the stochastic disturbances. Second, a novel optimal control strategy is proposed in this paper to effectively reduce the impact of stochastic continuous disturbances. To be specific, a novel excitation controlled power systems model with stochastic disturbances is built in the quasi-generalized Hamiltonian form, which is further simplified into a lower-dimension model through the stochastic averaging method. Based on this It&ocirc, equation, a novel optimal control strategy to achieve the intra-region probability maximization is established for power systems by using the dynamic programming method. Finally, the intra-region probability increases in controlled systems, which confirms the effectiveness of the proposed control strategy. The proposed control method has advantages on controlling the fluctuation of system state variables within a desired region under the influence of stochastic disturbances, which means improving the security of stochastic systems. With more stochasticity in the future, the proposed control method based on the stochastic theory will play a novel way to relieve the impact of stochastic disturbances.

This research paper presents a technique based on the non- linear optimization method for parameters of the power system stabilizers in multimachine power system. For the optimization or tuning of the parameters of PSS, the objective function is the maximization of the damping ratio of the critical modes of electro mechanical rotor oscillations. The objective of the coordinated parameter tuning is to globally optimize the overall system damping performance by maximize the damping of all both local and inter area modes of oscillations. The time domain simulation results of the multi-machine power system validate the effectiveness of the proposed approach. In this paper, the 10 machine 39bus New England system is used as the test system.

Optimal tuning of Power System Stabilizers (PSSs) parameters using Grey Wolf Optimization (GWO) algorithm is presented in this paper. Selection of the parameters of power system stabilizers which simultaneously stabilize system oscillations is converted to a simple optimization problem which is solved by a Grey Wolf Optimization (GWO) algorithm. The efficiency of the proposed method has been tested on two cases of multi-machine systems include 3-machine 9 buses system. The proposed method of tuning the PSS is an attractive alternative to conventional fixed gain stabilizer design as it retains the simplicity of the conventional PSS and at the same time guarantees a robust acceptable performance over a wide range of operating and system condition.

This paper presents the design of a sliding-mode perturbation observer-based sliding-mode control for stability enhancement of multi-machine power systems. The combinatorial effect of nonlinearities, parameter uncertainties, unmodelled dynamics and time-varying external disturbances is aggregated into a perturbation, which is rapidly estimated by a sliding-mode state and perturbation observer and then fully compensated by a sliding-mode controller in real time. The attractiveness of the sliding surface is analysed theoretically in the context of the Lyapunov criterion. The proposed control does not require an accurate system model and only one state measurement is needed. In addition, an over-conservative control effort can be effectively avoided via perturbation compensation. Simulation results for a three-machine power system and the New England power system verify the effectiveness of the proposed approach.

These days, the requirement for flexible and quick power stream control in the transmission framework is foreseen to increment later on taking into account utility liberation and power wheeling prerequisite. Diminishing the compelling reactance of lines by series remuneration is an immediate approach to build transmission ability. Nonetheless, power move capacity of long transmission lines is restricted by dependability contemplations. On account of the power electronic exchanging abilities as far as control and fast, more focal points have been done in FACTS gadgets regions and presence of these gadgets in transient security during transient flaws bringing about progress in power framework solidness. In this examination, a static synchronous series compensator (SSSC) is utilized to research the impact of this gadget in controlling active and reactive powers just as damping power framework motions in transient mode. The Proportional-Integral Controller (PI) controller is utilized to tune the circuit and to give the zero sign blunder. Static Synchronous Series Compensator (SSSC) is series reactive power remuneration to a power framework. The yield of a SSSC is series infused voltage, which leads or slacks line current by 90°, in this manner copying a controllable inductive or capacitive reactance. SSSC can be utilized to lessen the line impedance and upgrade the active power move ability of the line. With the boundaries and control, the SSSC is discovered successful to direct load voltage during abrupt difference in the heaps. The SSSC additionally furnishes stable activity with dynamic enlistment engine load and mitigates the insecure and swaying conduct that is coming about during the activity of remunerated Alternator with dynamic engine load.

Oscillatory 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 ...

Wind energy is one of the fastest growing energy resources of alternative power generation across the globe. Maximum number of generators in wind farm is provided with Doubly Fed Induction Generator (DFIG) due to its many advantages. The effects on small signal stability of system with distributed additional load, equipped with DFIG based wind farms, is presented here. The additional load added in the existing system is made same in value as the power generated by the wind farm. Different distributions of additional load are considered to determine the small signal stability of system with varying wind power penetration. The position of the negative real part of eigenvalues of system matrix helps to determine the best location for the integration of wind power for particular load distribution of additional load among different load buses. A new sensitivity based index has been introduced here to determine the maximum penetration level in terms of the system small signal stability. WSCC 3-machine 9-bus system is used for the study which is carried out in MATLAB.

Proposing novel power system stabilizers (PSSs) to damp effectively low frequency oscillations (LFOs) in multimachine power systems is an interesting topic which has attracted many attentions in recent years. Fractional order controllers (FOCs) have found new applications in power system stability issues, recently. In current paper, fractional order proportional integral derivative (FOPID) controller is employed in design of a practical stabilizer, which is based on integral of accelerating power. The authors have proposed an FOPID-based PSS2B stabilizer to improve the damping of LFOs in a multimachine power system. The design of FOPID-PSS2B is formulated as a nonlinear optimization problem in which adjustable parameters are optimized simultaneously via a modified group search optimization (MGSO) algorithm by minimizing integral of time multiplied squared error (ITSE) performance index. The damping performance of the proposed stabilizer is compared with the earlier stabilizers of PID-PSS2B and FOPID-PSS. The results of time domain simulations on a 3-machine 6-bus test system in MATLAB/Simulnik environment reveal that the proposed FOPID-PSS2B achieves superior damping performance in comparison with the former stabilizers. Besides, sensitivity analysis is carried out to evaluate the robustness of the proposed stabilizer. FOMCON toolbox is used for fractional order modeling and control.