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Transformer inrush current occurs due to the saturation of magnetic core. The magnetic characteristic of the core directly affects the inrush current waveform. Second harmonic and higher‐order harmonics are present in the inrush harmonic spectrum. A harmonic‐based method analysing the amplitude and phase of different harmonics is presented here. Based on the proposed method, the differences between the harmonic spectrum of new low‐loss and previous‐generation materials are investigated. Then, using the patterns of 1st to 10th harmonic phases, a novel method for inrush current detection is proposed. In the proposed method, possible patterns for the harmonic phases related to the inrush current are specified. The harmonic phases are compared with those specified patterns. In the case of matching, the inrush current condition is detected. To evaluate the theoretical principles, simulations are performed, also, the proposed method is applied to the field data to assess the practical performance, and results are presented. [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]

Automatic reconfiguration is one of the key actions in self‐healing distribution networks. In these networks, after detecting and isolating the faulted portion, an automatic reconfiguration procedure is performed to restore the maximum possible affected loads without further interruptions during repair operations. This procedure becomes more complicated in the networks with integrated distributed generation units as they can bring security challenges for the reconfigured network after a fault event. To overcome these challenges, a stochastic framework is proposed here. In this framework, the reconfiguration procedure is conducted with a fast and reliable method which is based on the graph theory. Besides, the security challenges of utilizing distributed generations after an event are highlighted. Then, since a faulted network is more prone to subsequent faults, different actions of changing the distribution generations output power, preventing the insecure increment of short circuit capacity, and also considering the loadability improvement are proposed in the reconfiguration framework. Then in the final stage, the vulnerability of the distribution system to the uncertainties of load demand is resolved through a chance‐constrained programming‐based approach. To see the performance of the proposed stochastic framework, it is tested on a standard test system and the results prove its goodness and applicability for real distribution networks. [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]

This paper proposes a novel fast and accurate method to mitigate the decaying DC (DDC) component from the fault current signal. At the first stage, it starts to identify the DDC parameters by integrating six sub-cycle samples of current signal considering the symmetry feature of odd harmonics. By receiving the next samples, the estimation of DDC parameters is updated and improved. This procedure continues until the integral of a full cycle current signal is calculated. To improve the accuracy of phasor estimation procedure, in each stage, by subtracting the DDC component from original current signal, the discrete Fourier transform method is applied to estimate the fundamental phasor. Performance of the proposed method for different DDC parameters and fault conditions is verified through various test studies, and its robustness against harmonics, noise, off-nominal frequency, and multiple DDCs conditions is also investigated. Besides, to demonstrate the reliability of proposed method in terms of dependability and security, it is implemented on the phasor estimation block of a distance relay. Three types of data including mathematical, simulated, and real power system signals are used to evaluate the performance of proposed method. Obtained results confirm the desirable performance of proposed method in various operating conditions. [ABSTRACT FROM AUTHOR]

Single-phase auto-reclosing (AR) scheme is widely employed in extra high voltage (EHV) transmission networks to quench transient faults without completely removing the faulted transmission line (TL). Long EHV TLs are commonly equipped with shunt reactors to reduce the Ferranti effect overvoltages. It is common practice to disconnect these reactors under the heavy load periods during the year. Considering this point, the AR technique should be able to work properly not only when the TL shunt reactors are in service, but also when they are disconnected. This paper puts forward a novel adaptive single-phase AR approach for shunt compensated TLs based on the general mathematical model of faulted phase voltage waveform after the line isolation, which is obtained by analytical analysis conducted on the TL's equivalent circuit. The effect of capacitor voltage transformer (CVT) on the voltage measurement is taken into account using a proper model for the CVT. Performing some data processing on the faulted phase measured voltage, useful features are extracted which are used by the support vector machine classifier to reliably detect the arc extinction instant. The proposed approach performance is evaluated by extensive simulation studies, accounting for different TL compensation schemes, transposition configurations, and arc conditions. [ABSTRACT FROM AUTHOR]

Unsecured operation of backup distance relay during an external fault results in removing a needed energy link and can jeopardise overall system stability. This problem that is well known as distance relay overreach is very likely during coupling capacitor voltage transformer (CCVT) transients mainly under high system impedance ratio (SIR) conditions. To tackle this challenging problem, a new methodology consisting of three stages is proposed in this study. It is capable of solving the overreaching problem which occurs under high SIR conditions, without sacrificing the operation speed of distance relay for inside the first zone faults. Comprehensive simulation studies are carried out to test the proposed methodology. The obtained results demonstrate its feasibility and effectiveness for practical applications in the power system. [ABSTRACT FROM AUTHOR]

In this study, economical options to meet the load demand of Hormoz Island as a green Island in future years, located in Iran, are investigated. For this purpose, construction of a new undersea transmission line (UTL) and design of a grid-connected hybrid renewable energy system (RES) are selected as two possible options. Therefore, the optimization problem is modeled as a minimization of cost function including the investment, replacement, operation, and maintenance costs of components, carbon tax, and cost of purchased power from the upstream network as well as the cost of loss of load. It is notable that the grid-connected hybrid RES consists of photovoltaic (PV) and wind energy systems with consideration of redox flow battery storage. The optimization problem is simulated for a 20 year planning horizon subject to technical and geographical constraints of RES. To simulate the problem, the annual hour-based data of wind, solar radiation, and load demand of Hormoz Island are used. Also, wind energy potential of the region is used for the selection of the best turbine for this island. Moreover, an imperialist competitive algorithm and an improved particle swarm optimization algorithm are applied to find the best size and design of the hybrid RES and also the best time to use the RES and the new UTL. Three different scenarios for optimum hybrid RES designing are determined to consider the effects of using the hybrid system to postpone the grid expansion investments. Two of these scenarios have 20 year planning horizon, and one of them optimizes the system for a special year with a specific predicted load demand. The obtained results revealed that the wind/PV/vanadium redox flow battery hybrid system is the best configuration, where the new UTL will be constructed in 2020 with zero load energy shortage. [ABSTRACT FROM AUTHOR]

Optimization techniques, specially evolutionary algorithms, have been widely used for solving various scientific and engineering optimization problems because of their flexibility and simplicity. In this paper, a novel metaheuristic optimization method, namely human behavior-based optimization (HBBO), is presented. Despite many of the optimization algorithms that use nature as the principal source of inspiration, HBBO uses the human behavior as the main source of inspiration. In this paper, first some human behaviors that are needed to understand the algorithm are discussed and after that it is shown that how it can be used for solving the practical optimization problems. HBBO is capable of solving many types of optimization problems such as high-dimensional multimodal functions, which have multiple local minima, and unimodal functions. In order to demonstrate the performance of HBBO, the proposed algorithm has been tested on a set of well-known benchmark functions and compared with other optimization algorithms. The results have been shown that this algorithm outperforms other optimization algorithms in terms of algorithm reliability, result accuracy and convergence speed. [ABSTRACT FROM AUTHOR]