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This paper investigates an optimal methodology for mitigating low-frequency oscillation concerns in power systems. The study explores the synergistic integration of a power system stabilizer (PSS) and a flexible alternating current transmission system (FACTS) to formulate an intelligent controller. A comprehensive analysis encompasses various PSS design strategies, including lead-lag (LL), proportional-derivative-integral (PID), and fractional-order proportional-integral-derivative (FOPID) controllers. The FACTS device selected for this investigation is a static VAR compensator (SVC), highlighting the exceptional efficacy of FOPID-based PSS over alternative strategies with a power oscillation damper. The study extends its scope to encompass a comparative assessment of two distinct optimization algorithms: the moth flame optimization (MFO) and the antlion optimization (ALO). The research is conducted using a single-machine infinite bus power system (SMIB) as the case study platform. A total of four diverse test scenarios are executed under varying operating conditions. The evaluation of the developed method employs six distinct performance indices to investigate the developed controller thoroughly. The outcomes reveal that the MFO-optimized FOPID-PSS and SVC controller outperforms other control schemes. This optimized configuration demonstrates substantial improvements across all performance indices. These findings underscore the superior capabilities of the proposed approach in enhancing power system stability and performance. [ABSTRACT FROM AUTHOR]

This paper proposes a novel method to find the optimal location of the shunt connected Flexible AC Transmission Systems (FACTS) such as Static Var Compensator (SVC) or Static Synchronous Compensator (STATCOM) to the power system for regulating voltage levels of all buses. Three indices include Voltage Drop Index (VDI), Total Voltage Drop Index (TVDI), and Total Voltage Drop of Network Index (TVDNI) are presented to find the location of the SVC. Also, to minimize the solution space, a ranking list will be established. For the case studies, the IEEE 14-bus test system is selected, and an SVC is located in the system. Simulations are done in two cases: network loads increase with constant coefficient and randomly. According to simulation results in both cases, the proposed method can identify the optimal placement of SVC, and the voltage drop due to increasing the load will be compensated. For the IEEE 14-bus test system, the optimal location of the SVC is bus 9. Variable loads are considered for 24 h, and SVC is installed at bus 9 to validate the introduced method. Results show the voltage level for all buses is compensated so that the voltage levels are higher than the minimum voltage level, i.e. 95%. [ABSTRACT FROM AUTHOR]

Given the concern for maintaining voltage stability in power systems integrated with renewable power systems due to a mismatch in generation and demand, there remains a need to invoke flexible alternating current transmission system (FACTS) devices in the distribution network. The present paper deals with identifying the locations of placement of a static var compensator in an experimental IEEE 14-bus system; the voltage drop in different buses in an IEEE 14-bus system is calculated by the standard formula. The total voltage drop in the network (TVDN) is also calculated as a reference. The ranking of buses in order of decreasing voltage drop is made, and the weak buses are identified as those showing the maximum or near-maximum voltage drop for the installation of a Static Var Compensator (SVC). The optimum usable size is calculated using a Genetic Algorithm approach to optimize the installation cost. After size optimization, installing a 2 MW solar generator is considered for the weak and most potential bus, which suffers from voltage drops or power loss. Based on the generator at the weakest bus, the total power loss in the network is calculated and compared with a similar method to assess the efficiency of the proposed model. Thus, the voltage stability enhancement problem is solved by applying a Genetic algorithm (GA) to optimize SVC size and using the Total Voltage Drop in Network (TVDN) method to identify weak buses in the systems. It is found that the performance of the proposed system is comparable with another existing system. It is further observed that a gain in power loss to 6.56% is achievable by adopting the proposed strategy, and the gain is better than the other system. [ABSTRACT FROM AUTHOR]

Today, Flexible AC Transmission Systems (FACTS) devices provide local reactive power support in load centers and keep bus voltages within safe operating limits. In particular, the single use of parallel FACTS devices may not improve the safe operating conditions of the system depending on the load conditions. Therefore, avoiding parallel FACTS devices' high costs is crucial and determining their optimal places in the system. For this, Static Var Compensator (SVC), one of the parallel FACTS devices, is used. This study investigated the effects of multiple uses of SVC on different load buses on the maximum load parameter of the multi-machine system in a 3-machine 9-bus power system. Moreover, bus-voltage profiles and their changes in active-reactive power are studied in detail. In this study, three analysis methods were used. These are the no SVC, the single use of SVC, and the multiple uses of SVC. The Power Systems Analysis Program (PSAT) was preferred for this simulation study. As a result of the study, using multiple SVCs increases the maximum loading parameter value and improves the bus-voltage profiles and active-reactive power changes compared to others. [ABSTRACT FROM AUTHOR]

This paper presents the application of Flexible Alternating Current Transmission System (FACTS) devices based on heuristic algorithms in power systems. The work proposes the Autonomous Groups Particle Swarm Optimization (AGPSO) approach for the optimal placement and sizing of the Static Var Compensator (SVC) to minimize the total active power losses in transmission lines. A comparative study is conducted with other heuristic optimization algorithms such as Particle Swarm Optimization (PSO), Timevarying Acceleration Coefficients PSO (TACPSO), Improved PSO (IPSO), Modified PSO (MPSO), and Moth-Flam Optimization (MFO) algorithms to confirm the efficacy of the proposed algorithm. Computer simulations have been carried out on MATLAB with the MATPOWER additional package to evaluate the performance of the AGPSO algorithm on the IEEE 14 and 30 bus systems. The simulation results show that the proposed algorithm offers the best performance among all algorithms with the lowest active power losses and the highest convergence rate. [ABSTRACT FROM AUTHOR]

Transient Stability is the capability of a system to be able to return to its normal state after experiencing large disturbances. The static var compensator (SVC) is a shunt device of the flexible AC transmission systems (FACTS) family using power electronics to improve transient stability in power system. For the SVC control, it is usually used a PI controller, although PI controller is simpler and cheaper but not suitable when power system is subjected to transient stability since power system become non-linear system. In order to overcome this problem, the PI controller combined with Fuzzy controller is designed. Two types of faults were considered for this study to examine the effect of the fuzzy-SVC controller on system transient stability, the proposed fault types are single line to ground fault and three lines to ground fault. The performance and behavior of the designed fuzzy controller compared with that of the conventional PI controller in term of terminal voltage, rotor angle, and transmission line active power. [ABSTRACT FROM AUTHOR]

Flexible AC transmission systems (FACTS) technology is widely adopted and utilized to maintain the performance of power systems. However, the improvements of power system performance achieved by FACTS devices depend on the right sizing and allocation of such devices. For technical and economic considerations, a FACTS device's location and size should be selected very carefully in order to maximize its benefits to the power system. In this paper, the sizing and location of a static VAR compensator (SVC) are optimally determined using a new optimization technique called lightning attachment procedure optimization (LAPO). The optimal allocation of the SVC is determined regarding the improvement of voltage deviation index and the reduction of total active power losses. The system is optimized in two cases: once without SVC installation in order to find out the optimal settings of the system that achieve the objective functions, and another time with SVC installation to determine its optimum sizes and locations by which the required objective functions are achieved. Then the system performance is analyzed after optimization with and without SVC devices to show the impact of the optimum sizing and location of the SVC on the system. The study is validated using the standard IEEE 30-bus system, while the developed LAPO is performed by MATLAB M-Files and the system performance analysis in different cases is performed by NEPLAN software. [ABSTRACT FROM AUTHOR]

Power quality is often defined as the electrical network's or the grid's capability to deliver a clean and stable power supply. Flexible AC transmission systems (FACTS) devices consist of power electronics circuits that's depend on the thyristor for controlling active and reactive power flows and to maintain the voltage within the allowable limits in normal and abnormal operating conditions. Static Var Compensation (SVC) is one of the most important FACTS devices, that's combined between shunt capacitor and shunt reactor, that's connect with the system by control setting. The control of reactive power by SVC module is depending on firing angle of thyristors. The shunt capacitor module can be called thyristor switched capacitors (TSC) and thyristor-controlled reactors (TCR), that's provide harmonic filters and/or dynamic shunt compensation. TSC operates with series bi-directional thyristor and a damping reactor to prevent the shunt resonance, the thyristors are used to control the capacitor to operate at the required value. TCR operates with series thyristor switch for control. SVC is easy and more accurate to operate with the medium voltage. SVC can be connected with the extra high voltage system via step-down transformer. This paper discusses the SVC to be uses to improve the power system quality, by adding the reactive power to the system. Also, this paper discusses the SVC control by using the MATLAB/Simulink software to discuss the step operation for the SVC with the power system. [ABSTRACT FROM AUTHOR]

This paper proposes the design of auxiliary-coordinated controller for static VAR compensator (SVC) and thyristor-controlled series capacitor (TCSC) devices by adaptive fuzzy optimized technique for oscillation damping in multimachine power systems. The performance of the coordinated control of SVC and TCSC devices based on feedforward adaptive neuro fuzzy inference system (F-ANFIS) is compared with that of the adaptive neuro fuzzy inference system (ANFIS) structure based on recurrent adaptive neuro fuzzy inference system (R-ANFIS) network architecture. The objective of the coordinated controller design is to tune the parameters of SVC and TCSC fuzzy lead lag compensator simultaneously to minimize the deviation of rotor angle and rotor speed of the generators. The performance of the system is enhanced by optimally tuning the membership functions of fuzzy lead lag controller parameter of the flexible AC transmission system (FACTS) by R-ANFIS controller. The training data for F-ANFIS and R-ANFIS are generated by conventional linear control technique under various operating conditions. The offline trained controller tunes the parameter of lead lag controller in online. The oscillation damping ability of the system is analyzed for three-machine test system by calculating the standard deviation and cost function. The superior performance of R-ANFIS controller is compared with various particle swarm optimization-based feedforward ANFIS controllers available in literature. [ABSTRACT FROM AUTHOR]

Increasing maximum power system loadability while maintaining bus voltages and line loadings constraints by flexible AC transmission system (FACTS) devices is one of the main issues in power system studies. One of the shunt FACTS devices widely used in power system is static var compensator (SVC). Its performance on power system is highly dependent on its number, location and operating point. This study presents a two‐level procedure to find optimal number, locations, and operating points of SVCs in a power system. At the first level, the goal is to maximise loadability of the power system. At this level, by using a method based on iterative process, applying SVCs to the power system, and increasing load factor, the optimisation algorithm seeks to find locations and operating points of SVCs that fulfil bus voltages and line loading constraints. This process continues until the increase in the number of SVCs does not lead to an increase in loadability. At the second level and for a certain number of SVCs, power system losses, total voltage deviations (TVD), and SVC installation cost are minimised at specific loadability. In this study, hybrid imperialist competitive algorithm and genetic algorithm (HICAGA) have been used for optimisation. [ABSTRACT FROM AUTHOR]

The increase in the scale and complexity of interconnected power systems leads to multiple electromechanical oscillations. Therefore, the electric network needs to be made more stable. One type of Flexible alternating current transmission systems (FACTS) devices, namely the static VAr compensator (SVC), can be installed at buses to increase the stability margins and dampen the power system oscillations by exchanging capacitive and/or inductive load to maintain and/or control specific parameters of electrical power systems. The efficiency and performance of the SVC depend on its optimal location. Consequently, seeking the optimal placement for SVC has become a key issue. In this paper, we propose a novel method to find the optimal location for the SVC based on a two-step approach. First, an energetic approach based on the combination of the controllability Gramian critical energy analysis with the balanced realization reduction technique is used to search for several feasible locations; then the transient stability is analyzed to compare and determine an optimal location through various test cases. The effectiveness of the proposed method has been demonstrated on the IEEE 39-bus England power system and compared with the modal controllability index. © 2016 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

In this study, power system stabiliser (PSS), static VAR compensator (SVC), and thyristor controlled series capacitor (TCSC) controllers are simultaneously used to increase the stability and damping of the oscillations of a multi‐machine power system. By SVC, the transferrable power in the steady state can be increased and the voltage profile can be controlled along the line. TCSC can regulate line impedance and therefore, increase the transferred power of the system. PSS is added to excitation system to enhance the damping of electric power system during low frequency oscillations. SVC, TCSC, and PSS can combine with each other for further damping and stability; therefore, their coordination is very important. Then, adaptive velocity update relaxation particle swarm optimisation algorithm is used to optimise the parameters of PSS, SVC, and TCSC simultaneous controllers. The robustness of the proposed algorithm has been tested on 16‐machine 68‐bus power system. [ABSTRACT FROM AUTHOR]

This paper presents a novel Flexible AC Transmission Systems (FACTS) placement method based on mixed integer quadratically constrained programming (MIQCP). The method is capable of allocating both Static VAR Compensator (SVC) and Thyristor-Controlled Series Capacitor (TCSC) either separately or simultaneously, to determine concurrently their numbers, locations as well as sizes. The optimization objective is to maximize loadability and minimize compensation. The proposed MIQCP formulation partially incorporates key quadratic constraints, which were absent in mixed integer linear programming (MILP) placement methods reported in the past. The authors demonstrate significant improvements in accuracy over past MILP methods, with case studies presented on the simplified Southeast Australian network, and on a large scale real-world power system, Powerlink Queensland's HV transmission network, with 886 buses and 1087 branches. In addition, results and observations for simultaneous allocation of multiple TCSCs and SVCs in these networks are demonstrated in this paper. [ABSTRACT FROM AUTHOR]

Recently, the number of electric-power facilities, including high-voltage direct current (HVDC) and flexible AC current transmission system (FACTS), has rapidly increased, owing to restrictions regarding the expansion of existing AC networks. Traditionally, a final site acceptance test (SAT) is conducted following controller performance verification in a factory acceptance test (FAT), based on an equivalent small network or voltage sources. Furthermore, several standards and guidelines related to the FAT and SAT of HVDC and FACTS have been published. Meanwhile, as the number of power electronic devices and the complexity of power systems increase, controller performance tests reflecting the wide area dynamic characteristics and control operation of adjacent devices should be required. However, a wide-area dynamic performance test (DPT) requires a large-scale real-time simulator and high-level operational technology. Owing to these difficulties, the definition, standard, procedure, and test protocol of hardware-in-the-loop simulation (HILS)-DPT, based on a large-scale power system, have not yet been established systematically, and only a few applications have been reported. This study aims to establish and propose procedures, a test protocol, and a methodology of HILS-DPT and large-scale power system modeling for testing. To this end, a case study was conducted to demonstrate the necessity of the DPT procedures and methodologies for the static VAR compensator controller installed at the Shin-Jecheon substation, an ongoing project undertaken the by Korea Electric Power Corporation, as of 2019. [ABSTRACT FROM AUTHOR]