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Faults in the power system should be detected as soon as possible. Otherwise, some defects in the protection system can result in imposing considerable destructive damage to the system equipment. The excitation system of a synchronous generator plays a significant role in the proper operation and control of the generator. Loss-of-excitation (LOE) may cause harmful effects on both the generator and power system. If LOE is not correctly detected, an unnecessary trip signal may be issued, resulting in the overloading of parallel generators and even a system blackout. Conventional techniques for detecting this fault are based on impedance measurement. Despite the simple structure of these techniques, they are sometimes unable to detect some faults correctly. The presence of flexible alternating current transmission system devices can significantly affect the impedance characteristic of the system and as a result, the operation of impedance relays. In this article, first, LOE and other bugs causing failures and errors in the protection of LOE are simulated in the presence and absence of a unified power flow compensator (UPFC), and parameters with different behavior are determined. Then, the most sensitive parameters are sorted using an intelligent method based on their sensitivity. Once the sort order table is obtained, the first two parameters are applied to a ground data handling neural network method, and LOE is detected. The simulation results show that the proposed algorithm is significantly reliable in detecting LOE faults. Moreover, LOE is detected very quickly in the presence or absence of the UPFC in the system by preventing the tolerance of electrical and mechanical stresses by the machine and system; thus, the maloperation of the protection system is avoided. [ABSTRACT FROM AUTHOR]

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]

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]

Power system protection and asset management have drawn the attention of researchers for several decades; but they still suffer from unresolved and challenging technical issues. The situation has been recently exacerbated in the wake of the ever-changing landscape of power systems driven by the growing uncertainty and volatility subsequent to the vast renewable energy integration, more frequent natural extreme events due to climate changes, increasing malicious cyberattacks, and more constrained transmission systems as the result of load growth and limited investments. On the opposite side, the proliferation of advanced measuring devices such as phasor measurement units, emerging electric and non-electric sensors, and Internet of Thing (IoT)-enabled data gathering platforms continually expand/nourish the databases; they hence offer unprecedented opportunities to take the advantage of data-driven techniques. Machine learning (ML) as a principal class of artificial intelligence is the perfect match solution to this need and has newly revoked many researchers' interests to tackle the problems excluding their exact/detailed models. This paper aims to provide an overview on applications of ML techniques in power system protection and asset management. This paper elaborates on issues pertaining to (1) synchronous generators, (2) power transformers, (3) transmission lines, and (4) special and system-integrity protection schemes. In addition to the opportunities offered by the ML techniques, this paper discourses on the barriers and challenges to the wide-spread application of ML techniques in real-world practices. [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]

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]

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]