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Integrating the self‐healing capability realizes the automated protection of smart distribution systems. This article presents a fault location scheme for low voltage (LV) distribution systems based on the information collected from the smart meters. First, a fault condition is detected and classified by processing the current signal at the secondary side of the distribution transformer by an intelligent electronic device. Then, the faulty feeder and section are determined by calculating the fault‐imposed component of nodal voltages. The reliable performance of the proposed scheme is verified through several case studies using a real semi‐rural distribution system. [ABSTRACT FROM AUTHOR]

With growing concerns over environmental degradation and climate change, the shipping industry is under increasing pressure to reduce its environmental impact. This has led to the development of green port initiatives in the field of maritime transport and logistics, which aim to promote sustainable practices and reduce the environmental footprint of ports and their operations. One of the key strategies for achieving this goal is the use of renewable energy technologies (RETs). This paper summarizes the potentials, challenges, and economic analysis of RETs applications in green ports, emphasizing those that require aquatic environments for operation, including floating photovoltaic systems, offshore wind turbines, and ocean energy. The paper investigates the concept of green ports and explores the feasibility of integrating RETs into these facilities. Also, the potential of the various RETs is presented in terms of technical and economic aspects and installed capacity. Additionally, due to high flexibility in electrical systems and compatibility with maritime transportation, the use of fuel cells in green ports has been discussed as a feasible solution for supplying power to ports (either as the primary or backup source). The findings of this study show that RETs can significantly contribute to achieving sustainable goals in the maritime industry and pave the way for the creation of more efficient and environmentally friendly ports. [ABSTRACT FROM AUTHOR]

This paper introduces an approach to analyse transient overvoltages during capacitor banks switching based on artificial neural networks (ANN). Three learning algorithms, delta-bar-delta (DBD), extended delta-bar-delta (EDBD) and directed random search (DRS) were used to train the ANNs. The ANN training is based on equivalent parameters of the network and therefore, a trained ANN is applicable to every studied system. The developed ANN is trained with extensive simulated results and tested for typical cases. The new algorithms are presented and demonstrated for a partial 39-bus New England test system. The simulated results show the proposed technique can accurately estimate the peak values of switching overvoltages.

Transformer switching is one of the important stages during power system restoration. This switching can cause harmonic overvoltages that might damage some equipment and delay power system restoration. Core saturation on the energisation of a transformer with residual flux is a noticeable factor in harmonic overvoltages. This work uses artificial neural networks (ANN) in order to estimate the temporary overvoltages (TOVs) due to transformer energisation. In the proposed methodology, the Levenberg-Marquardt method is used to train the multilayer perceptron. The developed ANN is trained with the worst case of switching condition, and tested for typical cases. Simulated results for a partial 39-bus New England test system, show the proposed technique can accurately estimate the peak values and durations of switching overvoltages.

Despite various advantages of integrating distributed generation (DG) units into distribution networks such as power loss reduction and voltage profile improvement, they may disrupt the performance of the conventional protection system due to bidirectional power flow and change of short‐circuit power. With the development of multi‐agent systems (MASs), intelligent protection schemes have been introduced that operate on the basis of data processing by a central controller. However, the possibility of communication failure and cyber attacks reduce reliability of these protection systems. To address this problem, this paper proposes an intelligent protection scheme that relies on peer‐to‐peer communication between agents in the first layer of the MAS. In the case of communication failure, the agents react to the fault condition by using the available data for similar conditions. The main advantages of the proposed scheme are reduction of number of employed agents by using only relay agents and no need for communicating with higher layers of MAS. Implementation of the proposed scheme in the ETAP simulation model of a 14 bus active distribution network shows that data exchange between relay agents properly modifies the operating time of the relays, resulting in protection coordination between main and backup protections. [ABSTRACT FROM AUTHOR]

The high‐surety power supply systems are gaining great attention to enhance the reliability of uninterruptable power supplies. A high‐resistance fault along a high‐surety power supply feeder results in a low fault current, making the conventional high‐surety power supply protection strategy ineffective. To address this problem, this paper develops a directional fault protection strategy for high‐resistance fault detection and faulty feeder identification. Using the intelligent electronic device, the feeder current is sampled and normalised. Then, the fault‐imposed component of the current signal is calculated. This component is added to the input of the forced Helmholtz oscillator to increase the sensitivity of the proposed protection scheme for the detection of high‐resistance faults. The output of the forced Helmholtz oscillator equation is adopted as the fault detection criterion because it is infinity for reverse faults while it is lower than 1 for forward faults, facilitating the fault detection. The developed strategy is local and can detect and classify both pole‐to‐ground and pole‐to‐pole high‐resistance faults. Also, it is effective for both unidirectional and bidirectional converters. The merits of the proposed protection strategy are demonstrated through several fault scenarios using a ±375 V high‐surety power supply system. [ABSTRACT FROM AUTHOR]

A high‐impedance fault (HIF) is mostly associated with the arcing phenomenon, and its main features are low current, randomness, non‐linearity, and asymmetry. The low fault current of an HIF is a major challenge for overcurrent‐based protection system of distribution networks. Power loss, potential fire hazard, and electric shock are consequences of an undetected HIF. This study presents a time‐domain HIF detection algorithm based on monitoring the substation current waveform. Using the Kullback–Leibler divergence similarity measure, the non‐linearity, and asymmetry features of two subsequent half cycles of the current waveform are quantified as the HIF detection criterion. A time duration‐based criterion is also used to distinguish HIFs from the load, capacitor, feeder, and distributed energy resource switchings and the voltage sag and swell events. The proposed scheme satisfactorily works in the presence of non‐linear loads. Also, it does not require the training data set, transformation, and calculation of harmonic/sequence components. Extensive time‐domain simulation case studies using the IEEE 13 and 34 node test feeders demonstrate the merits of the proposed HIF detection algorithm. [ABSTRACT FROM AUTHOR]

One of the major challenges in protection of the inverter-interfaced islanded microgrids is their limited fault current level. This degrades the performance of traditional overcurrent protection schemes. This paper proposes a fault detection strategy based on monitoring the transient response of the inverter current waveform using a transient monitoring function. To enhance the ability of the proposed fault detection scheme, an auxiliary control system is employed in addition to the main control system of the inverter. The proposed scheme can also differentiate asymmetrical and symmetrical fault conditions from normal load switching events and is effective for various inverter topologies (i.e., three/four-leg), main current limiting strategies, and all reference frames of the multi-loop control system. The merits of the proposed fault detection scheme are demonstrated through several time-domain simulation case studies using the CIGRE benchmark low voltage microgrid network. [ABSTRACT FROM PUBLISHER]

An important requirement for interconnecting distributed generation is anti-islanding protection. This paper uses the capabilities of two methods, application region (AR) and power imbalance AR, to efficiently adjust frequency-based relays. The proposed method gives a proper simple and nonexpensive solution to the synchronous distributed generation islanding detection problem. It employs the common protection devices: frequency or rate of change of frequency relays. These relays are adjusted in order to satisfy the anti-islanding protection and safe and abnormal frequency variation requirements and also to discriminate between islanding and nonislanding disturbances. The procedure is applied to a real system, which is a portion of the Isfahan Regional Electric Network in Iran, to show the effectiveness of the proposed approach. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

In this paper, a one-cycle control (OCC)-based approach for wind turbines equipped with doubly fed induction generators (DFIGs) is presented. The OCC is used to control back-to-back converter which includes generator-side converter and grid-side converter. The former is used for regulating generator speed, and the latter is used for controlling reactive power. Also, particle swarm optimization is used to improve the accuracy of parameters of PI controllers. The proposed approach is studied under different conditions, including load change, fault and nonlinear loads. Also, uncertainty of wind speed is considered. Moreover, a comparison between pulse width modulation (PWM)-based and OCC-based controllers is done. The OCC is a non-linear PWM method so its control technique turns a non-linear switch into a linear path. In contrast to the traditional PWM method, OCC control realizes PWM and fast/nonlinear control simultaneously by modulating the slope of the saw-tooth waveform. The simulation results show that accuracy and speed control of DFIG converter by OCC are superior in comparison with conventional control strategies from tracking reference signal and oscillations point of view. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]