Static Var Compensator Controller Research Articles

Damping Characteristics Improvement of Wind-PV Hybrid System by Coordinated Optimization of SVC-POD Controller Parameters

Background: With the increasing penetration of new energy resources such as wind farms and photovoltaic power plants, there is concern about the stability of power systems. Methods: Aiming at the low-frequency oscillation issue of the wind-PV hybrid system, a coordinated optimal design strategy based on Static Var Compensator (SVC) and Power Oscillation Damping (POD) control is proposed. Modal analysis is used to locate the controller, then the Whale Optimization Algorithm (WOA) is introduced to optimize the SVC-POD controller parameters. To solve the wind-PV hybrid energy system's low frequency oscillation issues, the damping ratio and angular velocity of the generator rotor are considered in the objective function. Results: Taking IEEE four-machine two-area system as an example, several working conditions are designed, including changing the power of the contact line. The eigenvalue analysis and simulation findings verify that the suggested proposed method can successfully raise the damping ratio of the system, keep the generator speed stable, and restrain the occurrence of low-frequency oscillation. Conclusion: Simulation results demonstrate that this method efficiently suppresses the lowfrequency oscillation and increases the robustness of the system.

FACTS placement for reactive power planning with weak node constraints using an improved symbiotic search algorithm

In this paper, an economically feasible and reliable operation of the IEEE 57 bus system for Optimal Power Flow (OPF) is proposed. The Improved Symbiotic Organisms Search (ISOS) algorithm is proposed for effective reactive power planning as an OPF issue. Further, the optimal position of Flexible AC Transmission Systems (FACTS) is taken into consideration, by including the existing system controlling variables like reactive power generators output, transformer tapping and capacitors connected at shunt. The objective of the work is two-fold; i.e., to reduce the energy loss and to enhance the voltage profile within the prescribed limit by ensuring the economic operation and investment cost of FACTS in the system. In this work, two FACTS devices like Static Var Compensator (SVC) and Thyristor-Controlled Series Controller (TCSC) have been taken into consideration. Voltage sensitivity indicator and reactive power flow are two tools that are utilised in order to locate weak nodes for the implementation of FACTS. Finally, the performance of the ISOS algorithm is compared with that of three other state- of-the -art optimization techniques, such as, Symbiotic Organisms Search (SOS), Differential Evolution (DE) and Teaching Learning Based Optimization (TLBO). A Non-parametric statistical analysis is also performed to investigate the dominance of the ISOS algorithm over others.

“Enhancing power system stability: an innovative approach using coordination of FOPID controller for PSS and SVC FACTS device with MFO algorithm”

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.

Analysis of the combined effects of SVC and SSSC controllers to improve power system stability

The primary challenge facing the electricity transmission system in the aftermath of the disruption is reestablishing stability. Through adjustment of the transmission parameters, the Flexible AC Transmission System (FACTS) devices have the potential to bring the system back into stable operation. It has been shown that using many FACTS devices together is more effective than using any one device alone. In this paper, the concept of coordination control between a Static Var Compensator (SVC) and a Static Synchronous Series Compensator (SSSC) is suggested in order to make the system more stable. The equivalent impedance of the line may be reduced by using the SSSC, which will also result in improved active power transfer capabilities for the line. A static var compensator, often known as an SVC, is used for shunt compensation in order to keep the bus voltage magnitude stable. When compared to the use of a single device, the use of SVC and SSSC coordinated control results in a much quicker arrival to the steady state response of the system. Both of these devices are controlled by using the same signal input tracking. It has also been seen that the system has resumed its previous synchronized state.

Rotor angle stability improvement by coordinated control of SVC and SSSC controllers

After a disruption in the power transmission system, the most crucial challenge is restoring the system’s stability. The FACTS devices can manipulate the transmission parameters to bring the system back into stable operation. This paper discusses the operational concepts and applications of FACTS in power systems such as the Static Var Compensator (SVC) and the Static Synchronous Series Compensator (SSSC). When combined with the other devices, the effectiveness of each individual device is increased. This paper proposes the coordinated control of SVC and SSSC to improve system stability. The SSSC can be utilized to lower the line’s equivalent impedance and improve its operational power transfer capabilities. The SVC is used for shunt compensation to maintain bus voltage magnitude. Furthermore, the steady-state response of the system is faster when SVC and SSSC coordinated control is employed compared to a single device. The resultant variable signal of the SSSC controller is tracked to control the SVC controller. A significant fault is introduced in the tie-line of the inter-area system to analyse and validate the proposed coordinated control. MATLAB/Simulation results are presented for the proposed approach, and also a real-time simulator is used to validate the simulation results.

A Guided Evolutionary Strategy Based-Static Var Compensator Control Approach for Interarea Oscillation Damping

Static Var compensator (SVC) has often been used in the power system industries to regulate the bus voltage and reactive power. With an increasing concern of the power system transient stability, the SVC has also been used to dynamically regulate the power flow for oscillation dampings in recent years. A guided surrogate-gradient-based evolutionary strategy (GSES)-based SVC control approach is proposed in this article to damp power system interarea oscillations. The GSES algorithm is used to train a reinforcement learning agent to learn the best decisions that control the SVC, with an objective of quickly damping interarea oscillations. The GSES algorithm brings many benefits such as easier, more robust, and efficient training with less required hyperparameters. Because the GSES can engage with multiple individual workers during the training process, parallel computation techniques are implemented in this research to accelerate the computational speed. To test the performance of the proposed GSES-based SVC controller, we compared this novel method with a supplementary SVC damping controller on two different test systems. Results indicate that the proposed GSES-based SVC control approach can effectively damp power system interarea oscillations. Especially, in some case studies, the proposed approach successfully saved the test system from a transient-instability-caused breaking down.

Intelligent wide‐area damping controller for static var compensator considering communication delays

SummaryThis paper utilizes a static var compensator in coordination with an intelligent online controller, to enhance the oscillation damping of the power system at various operating conditions and communication delays. For system identification, a linear identifier is used that ensures a low computational burden and facilitates its real‐time implementation. This identifier accurately estimates the system's local linear model using local measurements and continuously updates its parameters in real time to account for system's changing operational states. The learning rate of the identifier is also adaptively adjusted such that the stability of the learning algorithm and optimal speed of convergence are guaranteed. The location of the controller is selected based upon the controllability and bus voltage participation factors, and an effective feedback signal is obtained using the observability. An empirical expression has also been proposed to offset the effects of communication time delays caused due to use of wide‐area signals. Time‐domain simulations are performed on single‐ and multi‐machine power systems to check the efficacy of the proposed intelligent controller. The performance of the controller is compared with the residue‐based conventional controller and also with the recently proposed wide‐area damping controller.

Maximization of System Load-Ability and Voltage Stability Index Using Distribution Based Salp Swarm Optimization

Flexible Alternating Current Transmission Systems (FACTS) play a very prominent role in enhancing the performance of power system networks and in the quality up-gradation of power system by stabilizing the system parameters like voltage deviation, system security, power loss and system load-ability being a few to name. This work therefore handles two of the important performance parameters of a power system network namely power flow which is modeled as the System Load-ability (SL) and voltage profile which is represented as Voltage Stability Index (VSI). In this paper the maximization of VSI and SL of IEEE 30 Bus and 57 Bus networks have been exploited through the optimal placement of Thyristor Controlled Series Capacitor (TCSC), Static VAR Compensator (SVC) and Unified Power Flow Controller (UPFC) in the networks using the proposed and enhanced form of a recently developed meta-heuristic technique named as Salp Swarm Optimization (SSO). The outcomes of the simulations have been scrutinized with an established swarm-based optimization procedure.

Influence evaluation of signal transmission delay on supplementary damping controller for SVC in power system

Supplementary damping controller (SDC) for static var compensator (SVC) can be used to damp interarea low-frequency oscillations, but the influence of signal transmission delay on damping performance is generally neglected in the previous research. Because the delay may deteriorate damping performance or even cause instability for power system, this work intensively investigates the influence of signal transmission delay on input signal selection and parameter setting in SDC design. A novel evaluation method based on delay-dependent stability criterion and model order reduction is proposed to obtain the tradeoff between damping performance and delay margin for the SDC to be designed. Delay margin, determined by the proposed method, is taken as a critical index to evaluate the delay influence on SDC design. Case studies are carried out on two-area four-generator power system. Results show that for input signals with higher mode observability by residue method, such as current magnitude and active power of transmission line, delay margin decreases with the increase of SDC gain or delay variation ratio, which indicates that appropriately setting the gain can ensure SDC with better damping performance and larger delay margin.

Hybrid Algorithm for Coordinated Design of PSSs and SVC

The assessment of new coordinated design of Power System Stabilizers (PSSs) and Static Var Compensator (SVC) in a multimachine power system via statistical method is proposed in this paper. The coordinated design problem of PSSs and SVC over a wide range of loading conditions is formulated as an optimization problem. The Bacterial Swarming Optimization (BSO), which synergistically couples the Bacterial Foraging (BF) with the Particle Swarm Optimization (PSO), is employed to search for optimal controllers parameters. By minimizing the proposed objective function, in which the speed deviations between generators are involved; stability performance of the system is improved. To compare the capability of PSS and SVC, both are designed independently, and then in a coordinated manner. Simultaneous tuning of the BSO based coordinated controller gives robust damping performance over wide range of operating conditions and large disturbance in compare to optimized PSS controller based on BSO (BSOPSS) and optimized SVC controller based on BSO (BSOSVC). Moreover, a statistical T test is performed to ensure the effectiveness of coordinated controller versus uncoordinated one.

Optimal controller design for non-affine nonlinear power systems with static var compensators for hybrid UAVs

A generalized non-affine nonlinear power system model is presented for a single machine bus power system with a Static Var Compensator (SVC) or State Var System (SVS) for hybrid Unmanned Aerial Vehicles (UAVs). The model is constructed by differential algebraic equations on the MATLAB-Simulink platform with the programming technique of its S-Function. Combining the inverse system method and the Linear Quadratic Regulation (LQR), an optimized SVC controller is designed. The simulations under three fault conditions show that the proposed controller can effectively improve the power system transient performance.

A Novel Hybrid Chaotic Jaya and Sequential Quadratic Programming Method for Robust Design of Power System Stabilizers and Static VAR Compensator

This paper proposes a novel hybrid algorithm combining chaotic Jaya (CJaya) and sequential quadratic programming (SQP), namely CJaya-SQP, for solving the coordinated design problem of static var compensator (SVC) and power system stabilizers (PSSs). The CJaya serves as a global optimizer and the SQP as a local optimizer for fine-tuning the solution. In the proposed algorithm, chaotic maps are used to generate the initial solutions and control the search process. In order to prove the performance of the CJaya-SQP, a set of benchmark optimization problems is used where the results are compared with those of the basic Jaya and other recognized algorithms. The proposed optimization method is then applied for the optimal tuning of PSSs and SVC controllers in such a way that damping ratios and damping factors of the electromechanical modes are optimally improved. To illustrate the robustness of the CJaya-SQP-based coordinated PSSs and SVC controllers, the four-machine, two-area system is used. Eigenvalue analysis and nonlinear time-domain simulation vividly show that the CJaya-SQP-based coordinated controllers improve greatly the system’s dynamic stability with a robust damping of local and inter-area power oscillations.

A Novel Hybrid Sine Cosine Algorithm and Pattern Search for Optimal Coordination of Power System Damping Controllers

This paper presents an effective hybrid optimization technique based on a chaotic sine cosine algorithm (CSCA) and pattern search (PS) for the coordinated design of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. For this purpose, the design problem is considered as an optimization problem whose decision variables are the controllers’ parameters. Due to the nonlinearities of large, interconnected power systems, methods capable of handling any nonlinearity of power networks are preferable. In this regard, a nonlinear time domain-based objective function was used. Then, the proposed hybrid chaotic sine cosine pattern search (hCSC-PS) algorithm was employed for solving this optimization problem. The proposed method employed the global search ability of SCA and the local search ability of PS. The performance of the new hCSC-PS was investigated using a set of benchmark functions, and then the results were compared with those of the standard SCA and some other methods from the literature. In addition, a case study from the literature is considered to evaluate the efficiency of the proposed hCSC-PS for the coordinated design of controllers in the power system. PSSs and additional SVC controllers are being considered to demonstrate the feasibility of the new technique. In order to ensure the robustness and performance of the proposed controller, the objective function is evaluated for various extreme loading conditions and system configurations. The numerical investigations show that the new approach may provide better optimal damping and outperforms previous methods. Nonlinear time-domain simulation shows the superiority of the proposed controller and its ability in providing efficient damping of electromechanical oscillations.

A New Design Method for Optimal Parameters Setting of PSSs and SVC Damping Controllers to Alleviate Power System Stability Problem

This paper presents an improved Teaching-Learning-Based Optimization (TLBO) for optimal tuning of power system stabilizers (PSSs) and static VAR compensator (SVC)-based controllers. The original TLBO is characterized by easy implementation and is mainly free of control parameters. Unfortunately, TLBO may suffer from population diversity losses in some cases, leading to local optimum and premature convergence. In this study, three approaches are considered for improving the original TLBO (i) randomness improvement, (ii) three new mutation strategies (iii) hyperchaotic perturbation strategy. In the first approach, all random numbers in the original TLBO are substituted by the hyperchaotic map sequence to boost exploration capability. In the second approach, three mutations are carried out to explore a new promising search space. The obtained solution is further improved in the third strategy by implementing a new perturbation equation. The proposed HTLBO was evaluated with 26 test functions. The obtained results show that HTLBO outperforms the TBLO algorithm and some state-of-the-art algorithms in robustness and accuracy in almost all experiments. Moreover, the efficacy of the proposed HTLBO is justified by involving it in the power system stability problem. The results consist of the Integral of Absolute Error (ITAE) and eigenvalue analysis of electromechanical modes demonstrate the superiority and the potential of the proposed HTLBO based PSSs and SVC controllers over a wide range of operating conditions. Besides, the advantage of the proposed coordination design controllers was confirmed by comparing them to PSSs and SVC tuned individually.

A Novel Machine Learning-Based Framework for Optimal and Secure Operation of Static VAR Compensators in EAFs

A static VAR compensator (SVC) is a critical component for reactive power compensation in electric arc furnaces (EAFs) that is used to relieve the flicker impacts and maintain the voltage level. A weak voltage profile can not only reduce the power-quality services, but can also result in system instability in severe cases. The cybersecurity of EAFs is becoming a significant concern due to their cyber-physical structure. The reliance of SVC controllers on reactive power measurement and network communications has resulted in a cyber-vulnerability point for unauthorized access to the EAF, which can affect its normal operation. This paper addresses concerns about cyber attacks on EAFs, which can cause network communication issues in measurement data for SVCs. Three significant and different types of cyber attacks that are launched on SVC controllers—a replay attack, delay attack, and false data injection attack (FDIA)—were simulated and investigated. In order to stop the activities of cyber attacks, a secured anomaly detection model (ADM) based on a prediction interval is proposed. The proposed model is dependent on a support vector regression and a new smooth cost function for constructing the optimal and symmetrical intervals. A modified algorithm based on teaching–learning-based optimization was developed to adapt the ADM’s parameters during training. The simulation’s outcomes on a genuine dataset showed the strong capability of the proposed model against cyber attacks in EAFs.

Transient Stability Improvement of IEEE 9-Bus System Using Static Var Compensator

With increase in power demand over the last few decades, there has been a great expansion in power generation & transmission. But due to various disturbances, improper loading and environmental conditions the power systems are working near their stability limits which have become a power-transfer limiting factor. This in turn poses a threat to the stability of the system. Transient stability has been considered as one of the most important stability for a power system. In this paper Static VAR Compensator (SVC) has been discussed for reactive power control and hence improvement of transient stability and voltage profile. This paper incorporates IEEE-9 BUS test system with SVC controller using MATLAB Simulation.

State feedback control of advanced static var compensator using a five-level NPC inverter topology

This paper deals with the modeling and control of an advanced static var compensator (ASVC) using a five-level neutral point-clamped (NPC) voltage source inverter (VSI). The nonlinear state space model of the five-level ASVC is obtained from the d-q axis frame. The effectiveness of this compensator highly depends on the choice of the control strategy. The proposed state feedback control (SFC) technique is applied to adjust the ASVC Var flow with the AC transmission network and achieve DC voltage capacitor balance. The dynamic performance of the ASVC based SFC controller is evaluated under several operating conditions. The simulation results demonstrate that the proposed SFC control strategy is highly robust compared to the conventional Proportional-Integral (PI) control.

Application of multi-objective hybrid artificial bee colony with differential evolution algorithm for optimal placement of microprocessor based FACTS controllers

Increasing electricity demand, financial concerns for building new power stations have resulted in overloading, extreme power transfer, huge losses, reduced power eminence, consistency issues and voltage contour issues. To overcome these issues Flexible AC Transmission System (FACTS) controllers can be integrated into the transmission systems. Subsequently, it improves stagnant and vigorous enactment. Conversely, site, type and capacity of FACTS controllers have to be optimized to attain the aforesaid objectives. In this study, multiple objectives such as minimization of voltage deviation, losses, cost, and line loading index have been optimized using hybrid Artificial Bee Colony-Differential Evolution (ABC-DE). Three microprocessor controlled FACTS controllers for instance thyristor controlled series compensator (TCSC), static VAR compensator (SVC) and unified power flow controller (UPFC) have been placed optimally on IEEE 30 bus system. The outcomes of hybrid ABC-DE have been validated with the outcomes of particle swarm optimization (PSO). It implies that hybrid ABC/DE outperformed PSO for allocating FACTS controllers by optimizing multiple objectives concurrently.

An improved SVC control for electric arc furnace voltage flicker mitigation

The work focuses on the possibilities of improving the Static Var Compensator (SVC) control system for more effective reduction of the flicker effect. The studied SVC control system consists of an open control loop, which provides a fast response to dynamic changes in Electric Arc Furnace (EAF) power, and a closed control loop, which provides precise control to ensure the required value of the power factor in the Point of Common Coupling (PCC). The improvement consists in the use of alternative techniques for signal processing of input control variables. The first alternative technique is the use of Second Order Generalized Integrator (SOGI), which is also used in other related applications. The second alternative technique is to use the flicker weighting function, which corresponds to the function used to measure the flicker effect using a standardized flicker meter. Experimental laboratory equipment and theoretical model in frequency domain was used to verify the properties of the proposed techniques. To simulate the dynamic behavior of EAF, data measured from real operation were used, which were implemented into an experiment using VSC. Analysis of measured data and data obtained from laboratory apparatus shows high similarity. The experiments were carried out in several variants to reflect the differences in the various stages of the production process in the EAF. For all variants, the resulting flicker effect was evaluated and the individual techniques were compared with each other and with the results of other works.

Online estimation of control parameters of FACTS devices for ATC enhancement using artificial neural network

The deregulated electricity sector needs an improvement in the Available Transfer Capability (ATC) towards the maintenance of power network at balanced condition and to utilize the system in effective manner. Independent System Operator (ISO) maintains the ancillary services by ensuring the reliability of the power system. One of the major functions of ancillary service provider is to maintain the voltage and power flow at stable level. To improve the ATC, both the line power flow and bus voltage profile have to be modified and it is taken care by the ISO. The major limiting criterion for ATC is bus voltage profile. It is well known that the device Thyristor Controlled Series Compensation TCSC which is one of the Flexible AC Transmission System (FACTS) devices can modify the line flow by adjusting the line reactance and Static VAR compensator (SVC) can improve the bus voltage profile by injecting reactive power to the bus. In this research, an Artificial Neural Network (ANN) based estimation of control parameter of FACTS devices such as TCSC and SVC for ATC enhancement is used. The proposed approach uses two different ANN network to find the different TCSC and SVC control parameters to improve the ATC values without violating its voltage constraints for real time transactions. The ANN algorithms such as Radial Basis Function (RBF) as well as Back Propagation Algorithm (BPA) were used to find the TCSC and SVC Parameters and the results are compared. The proposed methods are demonstrated through Reliability Test System (RTS) of IEEE 24 bus. The simulation output represents the suitability of the anticipated method for Real Time estimation of FACTS devices control parameter settings for ATC Enhancement.