Energy storage systems (ESSs) are essential in future power systems because they can improve power usage efficiency. In this paper, a novel coordinated control algorithm is proposed for distributed battery ESSs (BESSs). The neighboring BESSs of a simulation system are grouped and controlled by a main control center. The main control center sends charging or discharging operation signals to each BESS. The primary objective of the proposed coordinated control scheme is to mitigate voltage and frequency deviations. In order to verify the proposed algorithm, the BESSs are connected to a distribution system of the Korea Electric Power Corporation. The results are compared with those obtained using uncoordinated control scheme with on-load tap changer considering aspects of power quality (voltage and frequency variation). The simulation results show that the voltage and frequency deviations are reduced with the proposed coordinated control algorithm.

The lifespan of a battery in battery energy storage systems (BESSs) is affected by various factors such as the operating temperature of the battery, depth of discharge, and magnitudes of the charging/discharging currents supplied to or drawn from the battery. In this study, the optimal location and size of a BESS are found for voltage regulation in a distribution system while increasing the lifespan of the battery. Various factors that affect the lifespan of a battery are considered and modelled. The problem is formulated as a multi‐objective optimisation problem with two‐objective functions. The first objective function calculates the energy losses in the system, whereas the second objective function represents the total investment cost of the distributed generator (DG) and BESS installations. Wind and solar DGs with uncertainties in their output powers are also considered with the BESSs. An elitist non‐dominated sorting genetic algorithm‐II with a utopian point method is used to solve the optimisation problem. Furthermore, an IEEE 906 bus European low‐voltage test feeder and eight test cases are considered for this study. The results show reduced losses and cost, improvement in the voltage profile, and extended lifespan of the batteries.

Microgrids experience significantly different fault currents in different operating scenarios, which make microgrid protection challenging. Existing intelligent protection schemes rely on the extraction of appropriate fault features using statistical parameters. The selection of these features is difficult in a microgrid because of its various operating scenarios. This study develops a convolutional neural network‐based intelligent fault protection strategy (CNNBIPS) for microgrids that inherently integrates the feature extraction and classification process. The proposed strategy is directly applicable to three‐phase (TP) current signals; thus, it does not require any separate feature extractor. In the proposed CNNBIPS, TP current signals sampled by the protective relays are used as an input to three different CNNs. The CNNs apply convolution and pooling operations to extract the features from the input signals. Then, fully connected layers of the CNNs employ the features to develop fault‐type, phase, and location information. To analyse the efficacy of the proposed design, we execute exhaustive simulations on a standard microgrid test system. The results confirm the effectiveness of the proposed strategy in terms of detection accuracy, security, and dependability. Moreover, comparisons with previous methods show that the proposed approach outperforms the existing microgrid protection schemes.

The increasing penetration of electric vehicles (EVs) in the distribution grid has established them as a prospective resource for ancillary services. These services require adequate control strategies for prompt and efficient operation. In this study, an energy management scheme (EMS) has been proposed to employ an off-board EV smart charger to support the grid during short-term variance of renewables and reactive load onset. The scheme operates by calculating power references for the charger instantaneously. The EMS incorporates a proportional power division methodology, proposed to allocate power references to the individual EVs connected to the charger DC-bus. This methodology considers the state-of-charge and battery sizes of the EVs, and it can aggregate energy from various types of EVs. The proposed scheme is compared with another power allocation method, and the entire EMS is tested under the scenarios of power mismatch and voltage sag/swell events. The results show that the proposed scheme achieves the goal of the aggregation of EVs at the charger level to support the grid. The EMS also fulfills the objectives of voltage regulation and four-quadrant operation of the smart charger.

Recently, the concept of microgrids has emerged in the world due to the integration of distributed energy resources (DERs) at the distribution end. The design of a reliable protection strategy is one of the top-most challenges associated with microgrids. This is because of the transition of microgrids between grid-tied and autonomous modes of operation. This paper presents a state-of-the-art microgrid protection scheme based on the Kalman filter (KF). The proposed scheme uses the one-end current signal of a distribution line for the detection and classification of faults. Firstly, the KF is applied to each phase of a three-phase current signal individually to generate residuals and total harmonic distortion (THDs). Next, the variations in the residuals and THDs of each phase are compared with pre-specified threshold values to detect the faulty events in the microgrid. As each phase is processed through KF individually, therefore, the proposed scheme is inherently phase segregated. Afterward, the KF is applied to extract the third harmonic component from the three-phase current and voltage signals. Then, the KF-based reactive power (KFBRP) is obtained from the extracted third harmonic components. Finally, the directional properties of the three-phase KFBRP are used to locate the faulty section in the microgrids. Extensive simulations in MATLAB/ Simulink software are performed for the grid-tied as well as the autonomous modes of operation under radial and meshed topologies. The results show that the proposed scheme is highly robust in all testing scenarios without any false tripping and blinding issues.