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The equal area criterion method is proposed for the power swing detection. Although this method is good for a single machine system, the method cannot distinguish the stable power swing from the unstable one in a multi machine system. In this paper, a novel method for distinguishing the stable power swing from the unstable one is proposed. In the proposed method the network is separated into the critical and noncritical machines. This method is performed by Digsilent software.

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An approach for assignment of the optimal location and tap changer adjustment related to Flux-Lock type Superconducting Fault Current Limiter with Tap Changer is used in this paper by debating the reduction of fault current flowing from each device and enhancement of reliability varying with customer type in a distribution network connected with Distribution Generation (DG). Three objective functions based on reliability index, reduction of fault current and number of installed MSFCL is systematized and a Nonlinear Time-Varying Evolution (NTVE) based Multi-Objective Particle Swarm Optimization (MOPSO) style is then formed in searching for best location and tuning of tap changer of MSFCL to meet the fitness requirements. A decision-making procedure based on Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is used for finding best compromise solution from the set of Pareto-solutions obtained through MOPSO-NTVE. In a distribution network as Bus 4 of Roy Billinton Test System (RBTS), comparative analysis of the results obtained from application of the Resistive SFCL (RSFCL) and MSFCL is presented. The results show that optimal placement of MSFCL than RSFCL can improve reliability index and fault current reduction index with less number.

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Electromechanical damping system is essential to ensure acceptable performance. However, when an error occurs in the transmission system, power transmission lines and buses voltage fluctuated severe, To eliminate the fluctuations in the power system stabilizer (PSS) is used to optimize the overall system performance, the problem of PSS parameters to an onlinear optimization problem with the objective function of the proposed conversion and optimization algorithms using Cuckoo (COA) and the cuckoo search algorithm (CS) optimization problem is solved. Stabilizers are adjusted so that the active power oscillations in the transmission system are considerably reduced. PSS parameters in network design and simulation of four standard generators under different working conditions are evaluated and analyzed. By comparing the results of the two algorithms in the network, COA efficiency and excellence in sustainable building several power generator system to the CS algorithm is proved.

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Wind powers are very unstable in voltage fluctuations, especially in short circuit error and sharp and sudden voltage drops, which one of its main reasons is the use of induction generators in these power plants and thus need to reactive power and high magnetizing current. To improve the ride_through voltage from WECS in error conditions and damping the oscillations of the induction generator rotor, a UPFC is used the controller FOPID is used in UPFC controllers for the first time. Since FOPID has two parameters more than IOPID, it has recently attracted much attention (needing more work and research motivation) as it gives more flexibility to a control system designing and a better opportunity to adjust the system dynamics, especially, if a system is to be controlled be a fractional system. The investigations indicate that controller FOPID adjusted by presented PSO algorithm, show improved dynamic performance than traditional PID and feedback controller in a wide range of operating conditions.

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The modeling of high frequency electromagnetic transients and the simulation of the voltage and the current distribution in the multi-winding traction transformer's windings due to these transient waves are very important. In the present article, in addition of presenting finite element models, the coupled field-circuit approach is proposed for the modeling of high frequency electromagnetic transients in a multi-winding traction transformer. The proposed method uses two-dimensional finite element models coupled with an external circuit to model the electromagnetic transient behavior of the multi-winding traction transformer. Afterwards, the results of the presented method have been compared with the results obtained from a complete three-dimensional finite element model as well as the detail model's results and the results are validated. Finally, the validated high-frequency model has been used to study the impulse response of the transformer. As shown, the proposed approach is a simple and fast method, and also has good accuracy in modeling of the impulse voltage distribution in the multi-winding traction transformer's windings.
 

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With the increasing expansion of power systems, random factors affecting the performance of these systems have also increased. Rising demand for electrical energy, along with the aforementioned random factors, has led to uncertainty analysis methods being of particular importance in analyzing the small signal stability of the power systems. In this paper, a method based on polynomial approximation for probabilistic small signal stability analysis of the power systems is presented. Since the correct determination of unknown coefficients has a direct effect on the accuracy of the polynomial approximation method, this paper presents a method that is able to determine these coefficients with more coverage on the probable input space of the problem and in addition, is able to maintain its efficiency even by increasing the number of random input variables. After determining unknown coefficients, the load flow results and system state matrix are determined for random changes of all loads and based on Hermit's polynomial approximation. Then, the eigenvalues ​​of the system are determined and the stability of the small signal of the system is probabilistically studied. In order to evaluate the accuracy and effectiveness of the proposed method, the IEEE 14-bus benchmark system is simulated in MATLAB software and the results of the proposed method is compared with the results of the two conventional methods of Point Estimation and Monte Carlo. Examination of the results has shown that the proposed method in this paper, in addition to validity, has good accuracy and high computational speed.
 

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The very low cost of renewable energy resources and the increase of the greenhouse gas emissions and fuel cost have led to a simultaneous increase in utilizing the renewable energy resources (RESs) and electric vehicles (EVs). In this paper, a mixed-integer linear programming (MILP) model is proposed for the stochastic unit commitment problem with the aim of minimizing the operation cost and the emission in the presence of EVs and RESs. EVs with the capability of vehicle-to-grid (V2G) can operate as energy storage units in the smart grid and, if necessary, be connected to the network as generation resources. In this paper, an aggregator is responsible for coordinating the charging and discharging of EVs. The RESs uncertainties has complicated the management of electric vehicles and the unit commitment problem. Therefore, in this paper, Monte Carlo simulation method is used for modeling the uncertainties of the wind and solar power and the load demand. The simulation results show that the simultaneous utilization of the proposed MILP model and the probability distance method for reducing the number of scenarios, can minimize the operation cost of thermal units and pollutant emissions while reduces the solution time, significantly

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In this paper, a new output feedback control method was used based on a linear matrix inequality to control the angular position of AC servo motor shaft. The proposed control method does not need to measure all of the AC servo motor statuses; it only uses the output feedback and is robust against the uncertain servo motor parameters and the disturbances applied to it. The proposed control method was compared in several scenarios with a Standard Internal Model Control-Sliding Mode Control (SIMC-SMC) method, 2-Degree-of-Freedom Internal Model Control-Sliding Mode Controller (2DOF-IMC-SMC) method, 2-Degree-of-Freedom Internal Model Control-Proportional-Integral-Derivative (2DOF-IMC-PID) method, Standard Internal Model Control-Proportional-Derivatives (SIMC-PD) method, and Internal Model Control-Proportional-Integral-Derivative-Extended State Observer (IMC-PID-ESO) method. The simulation results show that the proposed controller has desirable performance against disturbances and uncertain parameters of the AC servo motor compared with other mentioned controllers. This method relative to other controllers decreased the error of tracking the angular position of the servo motor to 30% .The simulation was performed in the Matlab Software. 

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Away to decrease the costs of generation and improve the performance of the grid generator, solving the problem of OPF based on line congestion management. As the power flow equation is nonlinear, this paper has performed the PSO algorithm to solve the OPF problem. By considering two technique this paper has performed the PSO algorithm for improving the performance. The first technique is to use a chaos generator to prevent PSO particles from sticking to local minimum points and the second is to consider the GSF in the WPSO algorithm structure so that the power passing through network lines can be simultaneously calculated and real power flow. Finally, the result of  WPSO-GSF algorithm which includes the bus voltage values, line losses, injection power to b buses, power passing through lines, total generation cost, setting electricity prices in two ways, UMP or LMP, depending on filling line capacity and calculating generators' profits has carried out .and also, to check the accuracy of the algorithm, the proposed method has been tested on IEEE 14-BUS, 30-BUS, 57-BUS standard networks, the results which indicate an increase in the speed and accuracy of the WPSO-GSF algorithm compared to other methods in improving the OPF problem.

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The paper presents an optimal and coordinated power oscillation damper based on a wind turbine and power system stabilizer (PSS) to maintain the power system stability and damp inter-area oscillations. The optimal and coordinated design of the PSS located at the generator site and the damper which was installed in the control section of the doubly-fed induction generator (DFIG) is defined as an optimization problem and simulations have been performed in MATLAB software environment. To determine optimal coefficients of the PSS and damper, the metaheuristic salp swarm optimization (SSA) algorithm was employed with an objective function that aimed to minimize the error caused by frequency deviations of two areas. Due to the use of wide-area measurement systems (WAMS) in the proposed damper to enhance controllability and observability of most of the oscillation modes, time delays resultant from the WAMS was also taken into account. Additionally, uncertainties of wind intermittency and time delay of WAMS were calculated probabilistically. The suggested method was applied to a six-machine two-area power system with a wind farm. The obtained simulation results highlighted and validated the superior performance and stability of the power system as a result of using the proposed method.

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Today, differential relays are used in order to protect power transformers against all kinds of faults and events. Despite advances in relay fabrication technology, the detection and discrimination of different events is still one of the most important challenges for the protection engineers in this field. In this paper, an intelligent hybrid method has been proposed to detect and classify internal electrical faults, external faults while saturating Current Transformers (CTs) and inrush current in transformers. First, the internal and external fault currents and the inrush currents of power transformers are simulated by the Real-Time Digital Simulator (RTDS) and its software package (RSCAD). Then, the sampled signals in different events are transmitted to MATLAB software for detection and discrimination. At this stage, using the Bayesian Classifier method, which directly evaluates the training data information, external faults are separated from the other operating conditions of the transformer. Then, other events such as inrush current and internal electrical faults will be distinguished from each other by Decision Tree (DT) and Support Vector Machine (SVM) methods. The results show that the proposed intelligent hybrid protection method has the ability to detect and classify different disturbances in transformers in real time state with appropriate accuracy, which is one of the main innovations of this study compared to other published research.

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In this paper, a new adaptive model predictive control based on Laguerre functions is proposed for the load-frequency control problem of a multi-area power system, in which the estimation of the internal model of the power system is updated online using the recursive least squares method. The use of the adaptive reduced-order internal model in the structure of model predictive control is the innovation of this research. In the studied system, the controller of each area is designed independently so that the stability of the overall closed-loop system is guaranteed. Numerical simulations for a three-area power system are carried out to validate the effectiveness of the proposed scheme and the results were compared with those of conventional model predictive control (MPC) and proportional-integral-derivative control (PID). The simulation results show that the proposed scheme performs better than PID and MPC in rejecting step load disturbance (with respect to nominal and uncertain parameters) and nevertheless, thanks to the use of the reduced-order model and Laguerre functions, reduces the computational burden significantly compared to conventional MPC.         
 

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This paper investigates the performance of differential protection of power transformers in the presence of internal faults, external faults, and cross-country faults in the presence of current transformers saturation, which is one of the main innovations of this study. Today, detection and discrimination of cross-country faults from other disturbances are one of the most important challenges facing protection engineers. Therefore, in this study, maximum overlap discrete wavelet transform has been used in order to accurately detect and classify these disturbances based on the extraction of energy coefficient indices of superior features. First, the cross-country faults, internal faults and external electrical faults, and inrush current phenomenon on the system under study in the EMTP software are simulated and differential current is sampled in different disturbances. Then, the mean indices of the sum of energy coefficient each level are calculated by MODWT by MATLAB software, and based on the values of indices, discrimination and classification of events are done. The results obtained from the simulations confirm that the proposed protection algorithm can detect and classify cross-country faults from other disturbances. Also, this method will improve the differential protection performance in different operating conditions and increase the reliability of power systems.

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In an islanded microgrid, power electronic converters are used to exchange power, and these converters have very low inertia, thus compromising the frequency stability of the microgrid. Virtual inertia control is used to improve the frequency stability of an islanded microgrid. The derivative control technique is usually used to implement virtual inertia control in the microgrid. Factors such as disturbance and uncertainty of parameters of the islanded microgrid compromise the performance of virtual inertia control and may cause system frequency instability. Therefore, the virtual inertia control structure, a complementary controller is needed that can weaken the effect of disturbance on the microgrid as much as possible and be resistant to the uncertainty of parameters of the microgrid. In this paper, a robust control method is used in a virtual inertia control structure that uses system output feedback. The proposed method is expressed based on linear matrix inequality and is proved based on the Lyapunov criterion. Among the advantages of the proposed method is the attenuation of disturbance, resistance to the uncertainty of parameters of the microgrid, and increasing the degree of freedom to control the system in this method. The results of the proposed method to improve the performance of virtual inertia control in several different scenarios by considering the uncertainty of parameters of the two-zone microgrid and disturbances on the microgrid are compared with several methods and the effectiveness of the proposed method in terms of improving frequency stability is shown.

 

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This paper presents a new online scheme of estimating power system transient voltage instability of interconnected synchronous generators using intelligent Bayesian theory based on wide area signals from WAMS data. For this purpose, by using online measurement of the system oscillatory signals gathered from WAMS technology and developing them as a series of input-output pairs data, the system dynamic category (stable/unstable) are achieved and used for Bayesian training. The proposed scheme is an online non-model-based technique with the ability of estimating binary decisions among the power system dynamic signals. In the case of evaluating effectiveness of the developed algorithm, by using an IEEE 39 test system, different fault events with the potential of transient voltage instabilities are investigated. In this case, considering two sampling data at pre-fault and post-fault occurrence moments, the system dynamic statues are estimated. Results present ability of the proposed scheme for fast and secure estimations of the system transient voltage instability.