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Summary: This 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. [ABSTRACT FROM AUTHOR]

The growing penetration of renewable energy resources in distribution networks demands for more active management tools. As a new controllable resource, dynamic network reconfiguration (DNR) can improve the flexibility of active distribution network, and in turn decreasing the operation cost of the distribution network and mitigating renewable distributed generation (RDG) curtailment. In this study, an optimisation model coordinating DNR with active network management (ANM) strategies is established, and the system structure security is evaluated. Considering the coordination of scheduling resources such as DNR switches, RDG active/reactive outputs, demand response and static var compensator, the model aims to minimise the comprehensive operation cost of distribution network and improve the consumption rate of RDG while satisfying the distribution network operation constraints. The model transformation method based on the second‐order cone relaxation and variable substitution linearisation is proposed, and the original no‐convex optimisation model is transformed into the mixed‐integer second‐order cone programming problem. Finally, the extended IEEE 33‐node distribution network is utilised to conduct simulation calculation, and the results demonstrate the validity of the proposed model and its transformation method. [ABSTRACT FROM AUTHOR]

This study presents a scheme for improvement of power quality in electrical distribution systems using a static VAr compensator (SVC). The switching of the SVC has been controlled with an objective to improve the overall power quality at the distribution level. The reduction of the degree of unbalance and improvement of power factor along with minimisation of harmonics injected into the system due to the operation of SVC are identified as the objectives of the SVC switching scheme. The proposed scheme can minimise a wider range of harmonics injected into the system without any external filter. The optimised switching angles have been calculated using the particle swarm optimisation technique. An artificial neural network has been designed to predict the optimum triggering angles and the performance of the scheme for fast changing loads has been evaluated in the laboratory using a data acquisition system. Practical evaluation of power quality has been carried out at each stage of simulation and experimentation to highlight the effectiveness of the proposed scheme. The results obtained from the proposed scheme have been compared with other recent works to prove the efficacy of the system. [ABSTRACT FROM AUTHOR]

Summary: The transient stability problem of a single‐machine infinite‐bus system with static var compensator is solved in this paper, where the static var compensator controller is designed by an improved backstepping method combining error compensation, adaptive backstepping control, and sliding mode variable structure control. Crucially, the error compensation term, which chooses in the step of virtual control by the adaptive backstepping method, is introduced to ensure that the system states are bounded, maintaining the nonlinearity of the power systems while also improving the speed of parameter identification. Meanwhile, the Lyapunov function is constituted step by step to achieve stability of the subsystem. In addition, a parameter updating law and a nonlinear control law are explicitly given to asymptotically stabilize the closed‐loop system. Finally, a simulation is used to illustrate the effectiveness and the practicality of the proposed control approach. [ABSTRACT FROM AUTHOR]

This study investigates three different techniques to mitigate the switching overvoltages (SOVs) in the microgrids. At first, the effectiveness of reactive power compensation devices, such as static var compensator (SVC), is evaluated. After that, the performance of the supercapacitor (SC), as an energy storage device, is studied. Finally, with the addition of the SVC to the SC, the possibility to mitigate SOV by compensating both active and reactive power simultaneously is investigated. SOVs result due to unsymmetrical switching operation during de‐energisation (disconnection) procedures. The μG two operational modes; grid connected mode and isolated mode, are considered. A small hydro generation unit and three variable speed, double‐fed induction generator‐based wind turbines are the main renewable power generation units in the tested microgrid system. Alternative Transient Program is used in this study for simulating the compensation device, the energy storage device and the investigated microgrid. The study shows that through the μG two operational modes, the SC has priority over the other two investigated mitigation methods. Furthermore, using the SC or SC with SVC, the results have more regular voltage waveforms. [ABSTRACT FROM AUTHOR]

Local latency adversely affects the stabilising performance of damping controllers especially in the two‐level control scheme. By considering both wide area and local latencies, this study presents the two‐level coordinated control which consists of wide area centralised and local controls of power oscillation damper (POD) and power system stabiliser (PSS) for robust power oscillation damping. The PODs are equipped with the doubly fed induction generator (DFIG) wind turbine, the solar photovoltaic generator (SPV), and the static VAR compensator (SVC). The centralised PODs of DFIG, SPV, SVC, and the centralised PSSs act as the primary damping controllers. When the communication failure occurs, the local PODs of such devices and the local PSSs are activated and used as the backup damping controllers. To achieve the damping performance and robustness, the parameters of centralised and local controllers are individually optimised based on the worst scenarios determined by the lowest damping ratio of target inter‐area oscillation modes. Study results in New England and New York IEEE 68‐bus system demonstrate that the proposed two‐level coordinated controllers are superior to the conventional two‐level controllers in terms of damping performance and robustness against various operating conditions. [ABSTRACT FROM AUTHOR]

In this study, the authors present an approach to validate the voltage schedule for operation of generation fleet within a balancing area managed by Independent System Operators/Regional Transmission Organizations or a balancing authority. An appropriate voltage schedule is an important requirement for the generator operators to maintain adequate VAR reserves and ensure the voltage stability. Based on current industry requirements, an empirical approach is developed to validate the voltage schedule following significant variations in generation pattern and load pattern, as possible results of integration of power generation from variable renewable resources or responsive demand. The approach can validate voltage schedule of generator fleet and transfer buses connected to the generator buses while monitoring the ranges of set‐point voltages and VAR levels of the generators. Moreover, they use the approach to investigate the impact of variations in the generation and load patterns on the voltage schedule in a real power grid. The findings are useful for an improved management of voltage stability, voltage schedule validation, and estimation of reactive power adequacy for operation support of future power grid with high penetration of renewables and responsive demands. [ABSTRACT FROM AUTHOR]

Electric arc furnace (EAF) is one of the largest non‐linear loads in power systems. It is highly time‐varying which leads to low‐frequency voltage fluctuations in the system, called flicker. Static VAr compensator (SVC) is always used in EAF plants to compensate the reactive power and reduce voltage fluctuations. The reactive power calculation unit is one of the most important units in SVC control system. Since SVC can only compensate the fundamental component, the calculated reactive power should not be sensitive to other harmonics. On the other hand, since the reactive power changes every half cycle, its calculation should be fast enough to track the changes. Hence, a calculation method with minimum delay and lowest harmonic sensitivity should be utilised to achieve an effective compensation. Among different already proposed methods for calculation of reactive power, differential method has the lowest delay. However, it is very sensitive to harmonics. In this study, Kalman filter is used to extract the fundamental components of voltage and current with a little delay and then they are used as inputs for the differential method. The proposed method is evaluated using some simulation signals and practical records from several EAFs in Mobarekeh steel company in Esfahan – Iran. [ABSTRACT FROM AUTHOR]

This study investigates the impact of different flexible AC transmission system (FACTS) devices on critical power quality (PQ) phenomena including voltage sags, harmonics and unbalance from the perspective of both mitigation effect and potential negative impact. The FACTS devices, including static VAR compensator, static compensator (STATCOM) and dynamic voltage restorers, are modelled in commercially available software PowerFactory/DIgSILENT to study their impacts on the critical PQ phenomena. Two control strategies, voltage regulation and reactive power compensation, are considered for STATCOM. For DVR, a PI‐controller is developed for the purpose of voltage sag mitigation. The merit of the proposed controller is presented by the dynamic response of during fault voltage and the capability of post‐fault voltage recovery. The study is carried out on a large‐scale generic distribution network. The impact of various devices on PQ phenomena is assessed using appropriate evaluation methodologies, and the results obtained with and without mitigation are presented and compared using heatmaps. [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]

This study presents gravitational search algorithm (GSA)‐based optimisation technique for the optimum co‐ordination of multi‐type flexible AC transmission system (FACTS) devices with the existing reactive power sources present in a connected power network. Three types of FACTS devices: namely, unified power flow controller, static var compensator and thyristor controlled series capacitor are used in the present problem and IEEE‐30 and IEEE‐57 bus systems are taken as standard test systems. The existing reactive power sources are reactive generations of the generators and transformer tap setting arrangements. The main objective of the present study is to reduce active power loss, system operating cost including the cost of FACTS devices and congestion in transmission network. The result obtained with the proposed GSA‐based approach is compared with the results obtained by genetic algorithm, differential evolution and particle swarm optimisation techniques. It is observed that by optimal placement of FACTS devices along with the optimal setting of the transformer tap arrangements and control of reactive generations of the generators line loss, system operating cost and transmission congestion is reduced significantly by the GSA‐based method compared with other methods. [ABSTRACT FROM AUTHOR]

The efficient operation of the present day power system is an important issue to satisfy the customer needs. To improve the performance of the existing power system, the flexible alternating current transmission system (FACTS) devices have been attracted by an engineering community with the expertise in power system. This article proposes the self‐adaptive firefly algorithm (SAFA) for placement of FACTS devices, which identifies the appropriate type, best possible locations and optimal parameters of FACTS devices. Static var compensator, thyristor controlled series compensator and unified power flow controller are considers as FACTS devices for their placement. The objectives are to improve the power system performance by placement of FACTS devices through minimising real power loss, improving voltage profile and enhancing the voltage stability. Effectiveness of the proposed SAFA is tested on standard IEEE 30 and IEEE 57 bus systems with different objectives. The results are compared with other approaches, which clearly indicate the effectiveness and usefulness of the proposed method. [ABSTRACT FROM AUTHOR]

Aiming at the problems that static var compensator cannot suppress the voltage flicker and the cost of static synchronous compensator is expensive, a three‐layer hybrid reactive power compensation scheme was proposed in this study based on the expert‐decision, differential‐slope voltage regulation, and the expert‐decision subsystem combining with fuzzy self‐tuning proportional–integral (PI) control. By switching in a dynamic load which can always change the bus voltage, the whole system was simulated under the much reactive power shortage and the less shortage. The simulation results verify the effectiveness of the proposed coordinated control method in the reactive compensation and the suppression of the voltage flicker. [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]

Absolute stability with the spatially defined linear time-invariant (LTI) state-space modelings is scrutinized by means of what we call the sequential Lyapunov approach, which possesses independent significance in stabilization when gain-scheduling control laws are adopted. Then, this theoretical result is exploiting for stabilization of individual generators via SVC actions. More precisely, by remodeling the perturbed swing equations of synchronous generators in multimachine networks through spatially defined LTI state-space expressions subjected to uncertainties and power disturbance, which are viewed as sector nonlinearities, we introduce frequency responses for coping with nonlinear power swing dynamics of individual generators. By sequentially relating the frequency responses to the circle criterion (substantially, the KYP theorem or the positive real lemma) claimed for LTI systems subject to sector disturbances, output feedback control laws for static VAR compensators are worked out to stabilize individual generators. The frequency-domain approach is also useful in steady-state specification besides stabilization in individual generators. Examples show efficacy of the suggested stabilization and steady-state specification technique. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

An adaptive damping control scheme based on classification and regression tree (CART) using wide‐area signals is proposed in this study. A family of robust controllers is designed off‐line and are used in real‐time after the corresponding operating point is retrieved from phasor measurement unit (PMU) data with CART interpolation. When the power system is operating precisely at a pre‐selected operating point, only the corresponding controller is active. When the power system is not exactly at the operating point, a combined controller is formed for damping. A 68‐bus, 16‐generator system is used as a test system. A thyristor‐controlled series capacitor, a static var compensator and an energy storage device are used as actuators, and remote PMUs frequencies as added inputs are employed as the example control. The simulation results demonstrate the effectiveness and robustness against the wider range of operating changes even without knowing precisely the model of disturbances that occurred in the dynamic system. [ABSTRACT FROM AUTHOR]

The time varying nature of electric arc furnace (EAF) gives rise to voltage fluctuations, which produces the effect known as flicker. Employing reactive power compensation devices such as static VAr compensator (SVC) is one of the main approaches to mitigate this phenomenon. By utilising prediction methods to forecast EAFs reactive power consumption for a half‐cycle ahead, performance of SVC can be enhanced substantially. This study proposes a rolling Grey model and a Grey–Markov method to predict the actual reactive power of Mobarakeh Steel Company, Isfahan/Iran. To investigate the efficiency of the proposed methods the results are compared with the results of EAFs reactive power compensation when no prediction method is employed. Furthermore, autoregressive moving average (ARMA) models with updating coefficients, which are studied in the literature are used to predict EAF reactive power. Various methods for updating ARMA coefficients including normalised least mean square, recursive least square method and an online genetic algorithm are used. By comparing the indices which are defined using the concept of flicker frequency and power spectral density, the superiority of Grey–Markov and rolling Grey model over the aforementioned prediction methods is investigated. [ABSTRACT FROM AUTHOR]

An adaptive damping control scheme based on the classification and regression tree (CART) using wide‐area signals is proposed. A family of robust multiple‐input multiple‐output controllers are designed offline and used in real‐time after the current operating point is retrieved from phasor measurement unit (PMU) data with CART interpolation. When the power system is operating close to a previously set operating point, only the corresponding controller is active. When the power system is not close to any previously set operating point, a combined controller is formed. A 16‐machine 68‐bus system is used for simulation test. Thyristor controlled series compensation, static var compensator and energy storage device are used as actuators and the remote PMUs frequencies are employed as added inputs in the example control. Simulation results demonstrate good damping performance of the proposed control method against a wide range of changes in operating state. [ABSTRACT FROM AUTHOR]

Hydro‐Québec's electrical transmission system is an extensive, international grid located in Québec, Canada with extensions into the northeastern United States of America. For large power systems such as this, one of the major issues is to maintain the steady‐state performance of the network. From this point of view, flexible AC transmission system (FACTS) devices could be effective tools to improve power system security by reducing the power flow on overloaded lines, which in turn would result in an increased loadability of the power system, reduced transmission line losses, improved stability and security and, ultimately, a more energy‐efficient transmission system. Therefore in this study, the authors will present the effects of different types of FACTS devices on the performance of Hydro‐Québec's power system. The optimal locations and rating of these FACTS controllers will be determined with a view to improving network security using an optimisation algorithm based on a genetic algorithm. The effects of six different FACTS devices including static VAR compensator (SVC), thyristor‐controlled series capacitor (TCSC), thyristor‐controlled voltage regulator (TCVR), thyristor‐controlled phase‐shifting transformer (TCPST), unified power flow controller (UPFC) and static synchronous compensator (STATCOM) with energy storage are compared. Using the presented results, the effects of different types of FACTS devices on the Hydro‐Québec network will be analysed and compared with those of a STATCOM equipped with energy storage from the viewpoints of static loadability and losses. [ABSTRACT FROM AUTHOR]

In this paper, the optimal tunning problem of parameters of a conventional lead-lag controller (LLC) and a fuzzy logic controller (FLC) based on the static Var compensator (SVC) is considered. The solution is obtained using an improved particle swarm optimization (IPSO) algorithm. The membership functions and scaling factors of the FLC and LLC parameters are optimized using the above-mentioned technique. The proposed controllers are settled down to an SVC that is installed at the middle of a transmission line connecting a single machine to an infinite bus system. Simulation results show the superiority of the optimized FLC compared to the optimized LLC and also when the SVC is without the supplementary controller under different disturbances and loading conditions. The simulations and analyses are implemented in MATLAB environment. © 2013 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc. [ABSTRACT FROM AUTHOR]

Wind shear and tower shadow produce a periodic pulse reduction in mechanical torque captured from wind energy resulting in wind energy conversion system (WECS) active power oscillations. In this study, an adaptive neuro‐fuzzy controller for static VAR compensator, used in power networks integrated with WECS, is presented to address the torque oscillation problem. The proposed controller consists of a radial basis function neural network representing a third‐order auto‐regressive and moving average system model and performing the prediction, and a main controller with adaptive neuro‐fuzzy inference system providing the damping signal. A modified two‐area four‐machine power network with WECS integration is applied to validate the proposed implementation, compared with conventional lead/lag compensation. Time‐domain simulations prove that the proposed controller can provide a damping signal to improve the active power oscillation and system dynamic stability, influenced by torque oscillations under WECSs synchronised operating condition. [ABSTRACT FROM AUTHOR]