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This study examines stability improvement of the power system which includes Double Feed Induction Generators (DFIGs) and Static Series Synchronous Compensator (SSSC). The proposed nonlinear controller is designed based on the terminal sliding mode control theory. A sliding mode observer is also developed to remove the need to access the information of all the state variables. The final closedloop of the power system modeling is robust against parameter variations and uncertainties. The limitations of the control signals in the process of controller design are also considered. The application of such a method increases the stability margins and results in higher robustness degrees. A comparison with other nonlinear approaches such as back-stepping and feedback linearization approaches is carried out. The results show the faster and more reliable convergence rate of the power system-controlled trajectories to reach back to the equilibrium point after occurring a sudden fault. The results are obtained by performing a simulation on the standard 39-Bus, 10 machines NEW ENGLAND power system. [ABSTRACT FROM AUTHOR]

This paper offers non‐linear control for enhancing the transient stability in power systems containing a photovoltaic (PV) and doubly fed induction generator (DFIG) by transient energy function (TEF) method and finite‐time observers. At first, the TEF method is utilized to enhance the transient stability in a power system containing a PV, DFIG, and synchronous generator (SG) by constructing a hybrid Lyapunov function. Then, the derivative terms in control are estimated with finite‐time observers. The main contribution of the research is the application of the TEF technique in the transient stability evaluation of a power system consisting of PV, SG, and DFIG. Another innovation of the research is the simultaneous control of DFIG and PV, whose uncertain parameters are estimated with the use of finite‐time observer. The proposed non‐linear control scheme is robust against changes in the configuration of the power system. In order to show the capability of this control scheme, time domain simulations are performed on the IEEE 9‐bus, and the NEW ENGLAND Standard 39‐Bus power system. Using the obtained result, some comparisons are made with the back‐stepping control scheme to clarify the superiority of the proposed method. The comparisons show that the proposed non‐linear control scheme can properly provide extra damping to reduce the first‐swing fluctuations in less time. The manuscript contains the new original results of the authors' research. In this article, to maintain and improve the transient stability, a new controller with simultaneous management of photovoltaic (PV) and doubly fed induction generator (DFIG) has been developed. The contributions of the paper are as follows. (1) The transient energy function (TEF) is obtained for the power system containing synchronous generator (SG) and DFIG. (2) The control laws are acquired with four PV and DFIG control variables. (3) The derivative parameters of the PV and DFIG controls by a finite‐time observer are estimated. [ABSTRACT FROM AUTHOR]

In this paper, the problem of improving the stability of the power system with DFIG and in the presence of SSSC using nonlinear method is discussed. The nonlinear controller is designed by the multi-input backstepping method with a sliding mode observer. This controller is applied simultaneously to the excitation system of synchronous generators and the rotor side converter in DFIG and sssc in a way that improves the stability of the power system compared to the linear and nonlinear methods described in this paper. The control coefficient matrices are adjusted using intelligent algorithms in such a way that the stability of the system is more optimized. Practical constraints on the system are considered in selecting the control inputs. The designed controller is robust to changes in the operating point and the location of the disturbance. The pei'formance of the designed controller in a 39-bus, 10 macliines NEW ENGLAND network including DFIG generators and in the presence of sssc is simulated and investigated using MATLAB software. [ABSTRACT FROM AUTHOR]

This study is concerned with the design of multi-input Dynamic Surface Control (DSC) to dynamic stability improvement of power systems which include both Doubly Feed Induction Generator (DFIG) and Static Synchronous Series Compensator (SSSC). The presented control method has a multi-input feature which acts on synchronous generators. To improve dynamic stability, the control law is developed by applying a suitable Lyapunov function. The coefficients of the proposed controller are determined by use of metaheuristic optimization algorithms. This optimal control law leads to a significantly improved performance in comparison with linear control. A particular low-pass filter is also introduced and applied to cancel the effects of additional undesired terms in the design method, leading to a simplified control form compared to the other available approaches in the literature. Implementing an adaptive parameter estimation scheme will result in the robustness of the proposed method. The effectiveness of the presented approach is investigated on a standard 39-Bus power system which includes DFIG and SSSC. [ABSTRACT FROM AUTHOR]

This paper aims to improve transient stability using the Ant Colony Optimization for Continuous Domains (ACOR). This improvement is obtained by solving the Transient Stability Constrained Optimal Power Flow (TSCOPF) problem and extracting the sensitivity coefficients. The presented costs minimization approach requires less execution time to manage energy resources efficiently and compared to other conventional methods, it also outperforms based on statistical indicators such as mean and standard deviation. Furthermore, the sensitivity analysis of the suggested method considers the active power generation of the generating units along with their terminal voltage, which notably decreases the operation cost and reduces risk to the power system. On the other hand, the application of ACOR algorithm can reduce the fuel cost of power system operation to 60,928.36 $/h with a decrease of 15.33 $/h compared to the conventional method with a standard deviation equal to 2.51 $/h and an execution time of 7.66 s. This strategy could be used in power system dispatching. This method is implemented on the New England 39 bus system, and the results demonstrate the method's efficiency compared to other conventional methods. [ABSTRACT FROM AUTHOR]

This paper deals with the optimal set of directional overcurrent relays using intelligent methods when the problem has multi-objective functions with different constraints. Due to the linear and nonlinear constraints in the coordination of the directional overcurrent relays, the method used is based on Pareto Envelope-based Selection Algorithm to obtain optimal values of plug setting, time multiplier setting, and relay characteristic curve by considering all governing constraints setting parameters of the network primary and backup relays. In this study, there is a simultaneous time reduction between the performance of the main and backup relays. Besides, in this method, while solving a multi-objective function without the need for weight factors, a penalty function is used to check the correct coordination of the primary and backup relays. The proposed method is implemented in two different standard networks, i.e. 3-bus and modified IEEE 14-bus networks. The results show the efficiency of the method used and the optimality of the values compared to other algorithms. [ABSTRACT FROM AUTHOR]

This paper presents the impact of simultaneous and coordinated control of the unified power flow controller (UPFC) and the doubly-fed induction generator (DFIG) on the multi-machine power system`s dynamic stability. All UPFC`s main basic PI controllers and its Power Oscillation Damping (POD) supplementary controller have been used. A more complete model of DFIG and both Rotor-Side Converter (RSC) and Grid-Side Converter (GSC) dynamics with their PI controllers are considered, too. UPFC and DFIG controllers are simultaneously coordinated and optimized with compromising between their control variables parameters. Particle Swarm Optimization (PSO) algorithm is used to optimize the objective function based on eigenvalues and damping ratio to reach the best parameters and variables of controllers of both UPFC and DFIG. During the studies of permanent and dynamic state, the thermal capacity of the lines and the nominal values of UPFC have also been considered. Simulation results in a 39-bus 10-machine New-England power system show the capability of the applied method. The results demonstrate that coordinated control of UPFC and DFIG tend to more damping system modes oscillation and more stability in the power system. [ABSTRACT FROM AUTHOR]

In this paper, improvement of the transient stability of a power system is investigated using Flexible AC Transmission System (FACTS) devices, i.e. Static Var Compensator (SVC) and Advanced Static Var Compensator (ASVC). The control method is based on the Lyapanov theorem and the Transient Energy Function (TEF). While the proposed method guarantees the damping of the fluctuations in the system, in order to increase the damping ratio, the intelligent optimization method of Genetic Algorithm (GA) is used. The parallel FACTS devices used in a Single Machine Infinite Bus (SMIB) are simulated. Also, changing in the topology of the power system can be applied to the proposed model. The simulation results show the effectiveness of the proposed optimal control method. [ABSTRACT FROM AUTHOR]

In this paper a neuro-fuzzy controller is proposed to enhance transient stability and increase critical clearing time (CCT) in the static synchronous compensator (STATCOM). For achieving this idea, first the controller is designed based on the Lyapunov energy function. In order to avoid complexity of computation and overcome system uncertainty a neuro-fuzzy controller is proposed. In this controller, Neural network determines the system rules and membership functions. In order to design a neural network and its training patterns, the energy function controller is used under various system conditions. This controller has learning abilities due to its robust fuzzy controller and neural network. Simulation results on the single-machine infinite-bus (SMIB) show that the neuro-fuzzy controller damps electromechanical oscillations and increases the critical clearing time. [ABSTRACT FROM AUTHOR]

With increase energy consumption in the world, power network development is necessary but creating a new transmission line is very costly. Therefore increasing line transmission capability is economic. We propose a method to FACTS device to the power network, in this paper and resulted in introducing decrease power network loss's and increase transmission capability with optimal choice and allocation of FACTS device by using genetic algorithm. We examine, proving this method by simulation IEEE6 bus system and using the genetic algorithm for optimal choice and allocation of FACTS device in this system. [ABSTRACT FROM AUTHOR]

This paper aims to improve transient stability using the Ant Colony Optimization for Continuous Domains (ACOR). This improvement is obtained by solving the Transient Stability Constrained Optimal Power Flow (TSCOPF) problem and extracting the sensitivity coefficients. The presented costs minimization approach requires less execution time to manage energy resources efficiently and compared to other conventional methods, it also outperforms based on statistical indicators such as mean and standard deviation. Furthermore, the sensitivity analysis of the suggested method considers the active power generation of the generating units along with their terminal voltage, which notably decreases the operation cost and reduces risk to the power system. On the other hand, the application of ACOR algorithm can reduce the fuel cost of power system operation to 60,928.36 $/h with a decrease of 15.33 $/h compared to the conventional method with a standard deviation equal to 2.51 $/h and an execution time of 7.66 s. This strategy could be used in power system dispatching. This method is implemented on the New England 39 bus system, and the results demonstrate the method's efficiency compared to other conventional methods. [ABSTRACT FROM AUTHOR]

This paper presents the comparative performance of neuro- Fuzzy controlled Voltage Source Converters (VSC) based Flexible AC Transmission System (FACTS) devices, such as Static Synchronous Series Compensator (SSSC), Static Synchronous Compensator (STATCOM), and Unified Power Flow Controller (UPFC) in terms of improvement in transient stability. In neuro-fuzzy control method the simplicity of fuzzy systems and the ability of training in neural networks have been combined. The training data set the parameters of membership functions in fuzzy controller. This Adaptive Network Fuzzy Inference System (ANFIS) can track the given input-output data in order to conform to the desired controller. The maximization of energy function of UPFC is used as an objective function to generate the training data. Proposed method is tested on a single machine infinitive bus system to confirm its performance through simulation. The results prove the noticeable influence of ANFIS controlled UPFC on increasing Critical Clearing Time (CCT) of system. [ABSTRACT FROM AUTHOR]

This paper presents a study about of a fuzzy Controlled STATCOM, which can be applied for mitigation of the voltage flicker in a distribution system. The voltage flicker is produced by a large variable load absorbing continuously changing currents such as an arc furnace. The DSTATCOM includes a voltage-sourced PWM inverter and its control system. The control strategy of the DSTATCOM plays an important role in maintaining the voltage flicker. Here, the DSTATCOM controller is designed with two types of controllers, linear proportional-integral (PI) and nonlinear fuzzy logic. The simulation of the DSTATCOM with 3MVar reactive power on a 25 KV distribution network is carried out in MATLAB/SIMULINK software. At the end of the paper, fuzzy controllers were evaluated by comparing its performance with the PI controllers. It is observed that the fuzzy controllers are very superior in mitigating the voltage flicker. [ABSTRACT FROM AUTHOR]