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The increase in renewable energy sources (RESs) in power systems is causing significant changes in their dynamic behavior. To ensure the safe operation of these systems, it is necessary to develop new methods for preserving transient stability that follow the new system dynamics. Fast-response devices such as flexible AC transmission systems (FACTSs) can improve the dynamic response of power systems. One of the most frequently used FACTS devices is the Static Var Compensator (SVC), which can improve a system's transient stability with a proper control strategy. This paper presents a reactive power control strategy for an SVC using synchronized voltage phasor measurements and particle swarm optimization (PSO) to improve the transient stability of a multimachine power system. The PSO algorithm is based on the sensitivity analysis of bus voltage amplitudes and angles to the reactive power of the SVC. It determines the SVC reactive power required for damping active power oscillations of synchronous generators in fault conditions. The sensitivity coefficients can be determined in advance for the characteristic switching conditions of the influential part of the transmission network, and with the application of the PSO algorithm, enable quick and efficient finding of a satisfactory solution. This relatively simple and fast algorithm can be applied in real time. The proposed control strategy is tested on the IEEE 14-bus system using DIgSILENT PowerFactory. The simulation results show that an SVC with the proposed control strategy effectively minimizes the rotor angle oscillations of generators after large disturbances. [ABSTRACT FROM AUTHOR]

This article presents the comparison of 3D and 2D finite element models of a power transformer designed for reactive power compensation stations. There is a lack of studies in the literature on internal electromagnetic phenomena in the active part of a transformer operated in these conditions. The results of numerical 2D and 3D calculations of no-load current and losses in the transformer core were obtained by using various methods and models. The impact of considering the hysteresis loop phenomenon on the calculation of core losses was investigated by using the Jiles–Atherton core losses model. The results obtained in the paper show that the model of the core must contain the areas representing the influence of overlappings on the no-load current and also on the flux density field in the core. The capacitive load of the transformer increases the flux density in the core limbs by several percent, so the power losses there must also increase accordingly. As a summary of the research, differences in the values of losses in each core element between the capacitive load and no-load conditions are presented. The results presented in this paper indicate that considering nonlinearity related to the magnetic hysteresis loop has a significant impact on the calculation of the core losses of power transformers. [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]

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]

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. [ABSTRACT FROM AUTHOR]