In the wake of increasing the share of renewable energy-based generation systems in the power mix and reducing the risk of global environmental harm caused by fossil-based generation systems, energy storage system application has become a crucial player to offset the intermittence and instability associated with renewable energy systems. Due to the capability to store large amounts of energy in an efficient way, redox flow batteries (RFBs) are becoming the energy storage of choice for large-scale applications. Vanadium-based RFBs (V-RFBs) are one of the upcoming energy storage technologies that are being considered for large-scale implementations because of their several advantages such as zero cross-contamination, scalability, flexibility, long life cycle, and non-toxic operating condition. This review presents the current state of the V-RFB technology for power system applications. The basic working operation of the V-RFB system with the principle of operation of its major components, the design considerations, and the limitations of each component are discussed. It presents technical information to improve the overall performance of the V-RFB by considering the materials of the cell components, modeling methods, stack design, flow rate optimization, and shunt current reduction.

With the rapid proliferation of cyber-physical systems (CPSs) in various sectors, including critical infrastructure, transportation, healthcare, and the energy industry, there is a pressing need for robust cybersecurity mechanisms to protect these systems from cyberattacks. A cyber-physical system is a combination of physical and cyber components, and a security breach in either component can lead to catastrophic consequences. Cyberattack detection and mitigation methods in CPSs involve the use of various techniques such as intrusion detection systems (IDSs), firewalls, access control mechanisms, and encryption. Overall, effective cyberattack detection and mitigation methods in CPSs require a comprehensive security strategy that considers the unique characteristics of a CPS, such as the interconnectedness of physical and cyber components, the need for real-time response, and the potential consequences of a security breach. By implementing these methods, CPSs can be better protected against cyberattacks, thus ensuring the safety and reliability of critical infrastructure and other vital systems. This paper reviews the various kinds of cyber-attacks that have been launched or implemented in CPSs. It reports on the state-of-the-art detection and mitigation methods that have been used or proposed to secure the safe operation of various CPSs. A summary of the requirements that CPSs need to satisfy their operation is highlighted, and an analysis of the benefits and drawbacks of model-based and data-driven techniques is carried out. The roles of machine learning in cyber assault are reviewed. In order to direct future study and motivate additional investigation of this increasingly important subject, some challenges that have been unaddressed, such as the prerequisites for CPSs, an in-depth analysis of CPS characteristics and requirements, and the creation of a holistic review of the different kinds of attacks on different CPSs, together with detection and mitigation algorithms, are discussed in this review.

The work presents the power-sharing in a standalone low voltage AC microgrid consisting of three parallel grid supporting inverters using a virtual impedance-based droop system. Typically, isolated microgrids suffer unique challenges regarding voltage, current, frequency regulation, power flow control, and power-sharing due to the absence of a stiff AC grid source. This work investigated the power flow and sharing technical challenges using three inverter-based distributed energy sources, three static loads, and one dynamic load. These distributed energy sources are interconnected with the loads using low voltage line impedance within the microgrid to implement the uneven power distribution. Furthermore, a distributed grid supporting control utilizing virtual impedance is proposed in this work to improve power-sharing. The microgrid model is developed with the MATLAB Simulink environment and validated using the Opal RT OP4510 simulator. The proposed technique ensured improved power-sharing and mitigated the effect of voltage drops introduced through a virtual impedance using combined positive and negative virtual.

This article proposes a cyberattack-resilient secondary frequency control (SFC) scheme for a stand-alone microgrid (MG) system. The proposed scheme is based on a hybrid system that employs an unknown input observer for state estimation, cyberattack detection and reconstruction, and a Type-2 fuzzy logic system for minimization of frequency deviation that may be caused by cyberattacks on the MG system. A cyberattack on the MG’s frequency measurement disrupts the operation of the SFC system and eventually compromises the frequency stability of the MG. The proposed approach shows an accurate estimation of the MG states and maintains the frequency of the MG within operating limits during various cyberattack scenarios. The practicability of the proposed hybrid scheme is validated using the Speedgoat real-time digital system simulator.

In the work reported in this paper, a novel application of the artificial bee colony algorithm is used to implement a virtual inertia control strategy for grid-connected wind energy conversion systems. The proposed control strategy introduces a new heuristic optimization technique that uses the artificial bee colony (ABC) algorithm to calculate the optimal gain value of an additional derivative control loop added to the control scheme of the machine side converter in a wind energy system to enable wind farms to participate in frequency control as specified by recent grid codes. This helps to minimize the frequency deviations, reduce active power deviation in the system, and increase the penetration level of wind energy in power systems. The study was performed in a restructured power system environment. The proposed control scheme and its robustness were evaluated using load–frequency analysis for three real-life transaction scenarios that can occur in an interconnected open-energy market and the validation was carried out using eigenvalue analysis. The results in this study show that the optimal gain of the proposed controller reduces the frequency deviations and improves stability and overall performance of the system.

In an islanded DC microgrid with multiple distributed generators (DGs), the droop control is employed to realize proportional current sharing among the DGs in the microgrid. The action of the droop control causes a deviation in the DC bus voltage which is exacerbated by the line impedance between the DG and the DC bus. In this paper, an advanced distributed secondary control scheme is proposed to simultaneously achieve accurate voltage regulation and cooperative current sharing in the islanded DC microgrid system. The proposed distributed secondary controller is introduced in the cyber layer of the system, and each controller shares information with neighbouring controllers via a communication network. The distributed technique maintains the reliability of the overall system if some part of the communication link fails. The proposed controller uses the type-II fuzzy logic scheme to adaptively select the secondary control parameters for an improved response of the controller. The sufficient conditions to guarantee the stability of the proposed controller are derived using the Lyapunov method. Comprehensive tests under different operating scenarios are conducted to demonstrate the robustness of the proposed control scheme.