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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]

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]

Intermittent power generation of wind turbines and photovoltaic plants creates voltage disturbances in power distribution networks which may not be acceptable to the consumers. To control the deviations of the nodal voltages, it is necessary to use fast dynamic control of the reactive power in the distribution network. Implementation of the power electronic devices, such as Static Var Compensator (SVC), enables effective dynamic state as well as a static state of the nodal voltage control in the distribution network. This paper analyzed optimal sizing and location of SVC devices by using genetic algorithm, to improve nodal voltages profile in a distribution network with dispersed photovoltaic and wind power plants. Practical application of the developed methodology was tested on an example of a real distribution network. [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]

Electric train system is a very large load for the power network. This load consumes a large amount of reactive power. In addition, it causes a massive unbalance to the network, which results in many problems such as voltage drops, high transmission losses, reduction in the transformer output ability, negative sequence current, mal-operation of protective relays, etc. In this paper, a novel real-time optimization approach is presented to adjust the static VAR compensator (SVC) for the traction system to realize two objectives; current unbalance reduction and reactive power compensation. A multi-objective optimization technique entitled non-dominated sorting genetic algorithm (NSGA-II) is used to fulfill the regarded objectives simultaneously. A comprehensive simulator has been designed for electric train network modeling that is able to adjust the parameters of SVC in an optimum manner at any time and under any circumstances. The results illustrate that the provided method can efficiently reduce the unbalancing in current as well as supply the demanded reactive power with acceptable precision. [ABSTRACT FROM AUTHOR]