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Even though shunt compensation of transmission lines (TLs) is a common practice to limit the overvoltages stemming from the Ferranti effect, it may cause transient and steady‐state resonant overvoltages when one phase is left open due to the single‐pole‐open condition following the temporary phase‐to‐ground (Ph‐g) fault. Furthermore, the existing shunt reactors potentially increase the duration of the secondary arc current at the fault point and hence prevent offering fast single‐pole reclosing. To exploit the mentioned issues, in recent studies, a neutral reactor is introduced, which is installed in the neutral point of the shunt reactors; nonetheless, obtaining the appropriate amount of it is remarkably challenging. In this paper, an optimal neutral reactor (ONR) is determined based on an optimization problem, which minimizes the neutral reactor cost subject to limiting both resonant overvoltages and the duration of the secondary arc current. In modelling, the Laplace domain is employed rather than the phasor domain to consider both transient and steady‐state conditions since this technique allows having better control over transient overvoltages as well as transient secondary arc. [ABSTRACT FROM AUTHOR]

Mal-operation of distance protection relays during power swing (PS) condition can endanger the power system stability. Therefore, it is crucial to distinguish between short-circuit faults and PS by a power swing blocking (PSB) function to prevent undesired tripping of distance relay. This paper develops a novel and straightforward PSB method based on the rate of impedance angle change (RIAC). Not only can the proposed approach fairly discriminate both symmetrical and asymmetrical faults from PS, but also it can appropriately preserve protection scheme security during PS under single-pole tripping (SPT) on a transmission line. Furthermore, there is no need to perform extensive dynamic stability studies for setting the PSB function parameters. Unlike the rate of impedance change approaches utilized two blinders, the developed approach only needs an inner blinder. Thus, it can be used for networks running near their operational limits. The proposed method is evaluated through a modified IEEE-PSRC benchmark system in PSCAD/EMTC environment. The obtained results verify superior performance of the proposed method to traditional impedance rate of change method under different scenarios. [ABSTRACT FROM AUTHOR]

This article presents a novel straightforward and real-time algorithm to measure power system frequency. The main idea of this approach is to improve accuracy of the estimated frequency during off-nominal frequency conditions. The proposed approach includes two stages: 1) the DFT algorithm is used to estimate voltage amplitude and phase angle by assuming that the frequency is the same as its value at the previous step, and 2) based on Taylor approximation and using the least error square algorithm, the error due to the frequency difference is calculated and thus the estimated frequency would be updated. One of the main features of the proposed approach is that it can be easily implemented on the available industrial hardware requiring low computational burden. The proposed approach is also robust against noise and harmonics and can track the deviations of the power system frequency as well. The performance of the proposed approach is evaluated through simulation studies and also verified based on implementing it on a prototype synchronizing relay. [ABSTRACT FROM AUTHOR]

Concerned with deploying zero-emission energy sources, reducing energy wasted through transmission lines, and managing power supply and demand, monitoring and controlling microgrids have found utter importance. Accordingly, this paper aims to investigate the efficacy of state estimation fusion for a synchronous generator as well as an induction motor in order to ameliorate system monitoring. A third-order nonlinear state-space model, that operates based on actual input data taken from the Smart Microgrid Laboratory, is assumed for each of the electrical machines. The model parameters are set according to the parameters of the electrical machines. A fusion structure based on the internet of things communication network, which is modified to increase uncertainty, is presented for fusing the state estimates. The data fusion topology is distributed and relies on two data fusion models. The first model is a set of state estimators, referred to as data input-feature output model. The second one fuses the estimators' outputs based on supervised machine learning methods, referred to as feature input-feature output model. The simulation results in MATLAB and Python show the efficiency of linear regression methods compared with other leveraged methods for data fusion. By comparing the results obtained from both simple and complex estimation filters, it can be deduced that combining simple filters, extended Kalman filter in this case, with simple data fusion methods, linear regression in this case, can produce much more accurate results in a short period of time. Besides, this study shows that the averaging operators are unsuitable for estimation fusion by referring to their convexity condition. • Regression methods can outperform other methods for the purpose of data fusion. • Simple filters combined with simple fusion methods boost state estimation accuracy. • The averaging operators are unsuitable for estimation fusion due to performing convex fusion. [ABSTRACT FROM AUTHOR]

Power transformers are of the most critical and expensive equipment in the power system industry. Meanwhile, they are exposed to a variety of faulty and abnormal operating conditions. Therefore, to prevent extension of these events they are protected by different protective schemes. Among the various types of the transformer faults, detecting turn-to-turn faults is the most challenging one for the protection systems. Industrial experiences and standard documents reveal that the existing protection systems include severe shortcomings, and still more efforts are required to offer a reliable method for detecting such faults. To this end, this article puts forward the proposal of a novel turn-to-turn fault detection method to satisfy the basic protection requirements of dependability, security, and speed. This method properly detects the low-level turn-to-turn faults while is stable during system transients and external faults. Performance of the proposed method is evaluated through various experimental and simulation studies. The obtained results verify superior operation of the proposed method under different faults and conditions. [ABSTRACT FROM AUTHOR]

Here, an optimization framework is proposed for the service restoration (SR) problem in distribution networks based on mixed‐integer second‐order cone programming (MISOCP). The objective function is to minimize (i) curtailed loads, (ii) the number of switching operations, (iii) crew dispatching cost, and (iv) operational cost. A novel approach is developed for the optimal switching crew routing (SCR) to perform the manual switching operations in a short time. Self‐healing actions including (i) network reconfiguration, (ii) load shedding, (iii) adjusting the output power of the dispatchable distributed generations (DGs), and (iv) the optimal tap setting of the voltage regulation devices are adopted in the SR strategy. Both the voltage dependency and the uncertainty nature of loads are modelled. Besides, the switch failure scenario is considered in the proposed model to deal with real operating conditions. Hence, the developed optimization framework offers the most robust SR solution. The simulation studies are performed on an actual 87‐bus system in MATLAB/Yalmip environment by adopting Gurobi solver. The obtained results verify that the proposed model enhances quality of the solution in terms of SR process time compared to the other existing models. [ABSTRACT FROM AUTHOR]