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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]

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]

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]

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]

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]