10 - DC microgrids for electric vehicle wireless charging

Stability analysis of islanded DC microgrid for the proposed distributed control strategy with constant power loads

The advanced connection requirements of industrial automation and control systems have sparked a new revolution in the Industrial Internet of Things (IIoT), and the Supervisory Control and Data Acquisition (SCADA) network has evolved into an open and highly interconnected network. In addition, the equipment of industrial electronic devices has experienced complete systemic integration by connecting with the SCADA network, and due to the control and monitoring advantages of SCADA, the interconnectivity and working efficiency among systems have been tremendously improved. However, it is inevitable that the SCADA system cannot be separated from the public network, which indicates that there are concerns over cyber-attacks and cyber-threats, as well as information security breaches, in the SCADA network system. According to this context, this paper proposes a module based on the token authentication service to deter attackers from performing distributed denial-of-service (DDoS) attacks. Moreover, a simulated experiment has been conducted in an energy management system in the actual field, and the experimental results have suggested that the security defense architecture proposed by this paper can effectively improve security and is compatible with real field systems.

In direct current (DC) microgrids, traditional droop control methods facilitate power sharing and stabilize bus voltage. However, this communication‐less approach is constrained by challenges including insufficient voltage restoration and imbalances in battery state of charge (SOC). This paper introduces a novel communication‐less control strategy designed to address these limitations in photovoltaic energy storage system (PV‐ESS) DC microgrids. This method assigns the energy storage unit (ESU) closest to the critical load as the ‘master unit’ setting its output voltage to nominal levels. This master unit injects an alternating current (AC) signal into the DC bus, with the signal frequency modulated by its SOC and output current. Additional ESUs, referred to as ‘slave units’ adjust their output currents based on the frequency of the AC signal and their local SOC. Furthermore, the master unit utilizes a logical signal based on its SOC to switch the photovoltaic module between droop control mode and maximum power point tracking (MPPT) mode. Stability analysis verifies the robustness of the proposed method, and simulation results demonstrate that it surpasses conventional droop control approaches. Specifically, the proposed method enhances load‐sharing precision, minimizes voltage deviation, and ensures SOC equalization across the DC microgrid without the need for communication links. © 2026 Institute of Electrical Engineers of Japan and Wiley Periodicals LLC.

Energy management in DC microgrid with an efficient voltage compensation mechanism

Nowadays, cyber-attacks are immoral ways to disturb power grids and make them devitalized or unstable. To avoid such issues, detection and estimation of cyber-attacks are essential in modern power utilities. This paper investigates a new nonlinear Kalman filter, called Spherical Simplex Radial Cubature Kalman Filter (SSRCKF), as a reliable and accurate estimator to detect cyber-attacks in nonlinear Direct Current (DC) microgrids (MGs) with Constant Power Loads (CPLs). The developed nonlinear Kalman filter offers a high resilient State Estimation (SE) performance in presence of noise as well as desired accuracy, and low computational burden. The SSRCKF is modified for the attack detection issue by augmenting the occurring attacks to the original nonlinear dynamics. The developed SSRCKF approach is deployed to estimate the DC MG states in the presence of Denial-of-Service (DoS) and data integrity attacks. Simulation results show that the presented filter estimates the DC MGs states of the system immediately after the attack.

The rapid development of electric vehicles (EVs) increases the power demand, which causes an extra burden on the public grid, increasing the load fluctuations and, therefore, hindering the high penetration of EVs. In this paper, a real-time rule-based algorithm for electric vehicle (EV) charging stations empowered by a direct current (DC) microgrid is proposed. Such a DC microgrid model consists of EVs, an electrochemical storage system, a public grid connection, and photovoltaic sources. The EV charging station model is based on data-driven modelling while its management model takes into account discrete events. This paper focuses on power management strategy of an EV charging station under power limitation and considers most of the drivers’ choices. The EV charging system topology is presented and common problems during an EV charging process are discussed, e.g., disconnection operation, standby mode, shedding, and restoration operation. Furthermore, the proposed power management deals with the uncertainties of EV drivers’ behavior considering arbitrary and random choices through the human–computer interface. The simulation results obtained under MATLAB/Simulink verify the feasibility of the proposed management strategy that presents a good performance in terms of precise control.

The national electric utility of Greece has recently installed and put in operation a modern Energy Management System (EMS), This paper presents the evolution of the Supervisory Control and Data Acquisition (SCADA) system of the EMS during its two years of commercial operation. It classifies all the improvements implemented during this period in 3 areas: telecommunications, man-machine interface and core SCADA functions.

This research project studies: 1) control and operation of islanded DC Microgrids (MG) including simultaneous Load Sharing (LS) and voltage regulation (VR) through a decentralised control method, 2) energy management and applications of Battery Energy Storage Systems (BESS) in islanded DC MGs, 3) integration of DC MGs into the AC network, and 4) power balance in hybrid AC/DC MGs.

DC microgrids have gained a lot of interest recently due to increasing dc loads such as electric vehicles and the penetration of renewable energy sources (RESs). However, DC microgrids face challenges concerning bus voltage fluctuations, which severely impact the system stability when subjected to uncertainties of load and RESs. This paper focuses on maintaining the stability of a DC-bus through voltage control for a dc islanded microgrid using the concept of cascade double-loop control. The rule in cascade double-loop control is based on a proportional-integral (PI) controller tuned through a new nature-inspired African vulture optimization algorithm (AVOA). The paper presents a comparison of the performance of the African vulture optimization algorithm against particle swarm optimization (PSO) under several operating conditions. The simulation considers actual data for the solar irradiance and temperature and sudden load changes. The system is implemented on MATLAB/Simulink. The results demonstrate that the AVOA-based PI controller performs better in voltage regulation than the PSO-based PI controller.

The charging infrastructure plays a key role in the healthy and rapid development of the electric vehicle industry. This paper presents an energy management and control system of an electric vehicle charging station. The charging station (CS) is integrated to a grid-connected hybrid power system having a wind turbine maximum power point tracking (MPPT) controlled subsystem, photovoltaic (PV) MPPT controlled subsystem and a controlled solid oxide fuel cell with electrolyzer subsystem which are characterized as renewable energy sources. In this article, an energy management system is designed for charging and discharging of five different plug-in hybrid electric vehicles (PHEVs) simultaneously to fulfil the grid-to-vehicle (G2V), vehicle-to-grid (V2G), grid-to-battery storage system (G2BSS), battery storage system-to-grid (BSS2G), battery storage system-to-vehicle (BSS2V), vehicle-to-battery storage system (V2BSS) and vehicle-to-vehicle (V2V) charging and discharging requirements of the charging station. A simulation test-bed in Matlab/Simulink is developed to evaluate and control adaptively the AC-DC-AC converter of non-renewable energy source, DC-DC converters of the storage system, DC-AC grid side inverter and the converters of the CS using adaptive proportional-integral-derivate (AdapPID) control paradigm. The effectiveness of the AdapPID control strategy is validated through simulation results by comparing with conventional PID control scheme.

The performance and output of PV cells depends upon different factors: irradiance, shaded modules, shadow, temperature, inverter capability, wind speed, wind direction and the number of PV installed are one of them. Maximum Power Point Tracking (MPPT) is required to control various effects caused by one of the aforementioned factors. Researchers have employed many MPPT techniques. However, these techniques showed some limitations such as slow response and inability to be remotely controlled. This has been observed during the higher number of PV grid connected inverters installed in some regions of Rwanda where the power generated via peak conditions sometimes exceeds the transmission capacity limits. In this case, the classical MPPT cannot respond efficiently. With the aim to alleviate these issues, the paper uses perturb and observe MPPT with SCADA viewer software so that inverter can operate with its design limits. This involves the de-rating and control of inverter capability curve. The derating and control of an inverter capability curve are one of strategies to mitigate the above-mentioned problem in order to stabilize voltage and restricts harmonic current injection to utility grid. This paper shows a designed model that was simulated in Matlab with MPPT which is perturb and observe (P&O) and experimentally validated. In addition to Rwanda utility grid, the experimental set up used a SCADA viewer and communication tools to acquire data concerning the PV system. This allowed to perform the following tasks: automatic data acquisition, notification of voltage variation and display active and reactive power being sent or being consumed, grid fault detection, islanded mode detection and remotely shut down the system as long as Wide Local Area Network (WLAN) is present. The experimental results showed that any design of grid connected inverter having any type of MPPT technique must have a capability curve to figure out the operating zones of the inverter in different circumstances and specified the tolerance range of crucial parameters with its validation through SCADA viewer software.

Direct Current (dc) microgrids due to their efficiency and energy savings are being deployed to provide power for servers in Internet of Things (IoT) data centers, in more electric aircrafts (MEA), electric ships and in rail systems round the word. In this paper, Takagi-Sugeno fuzzy inference method is used to establish a Lyapunov stability candidate for a 380 V ring bus dc microgrid modeled with Matlab. To determine suitability of using powerline communication (PLC) to monitor stability condition on the 380 V dc microgrid, impact of distortion caused by microgrid constant power loads (CPL) on signals transmitted over the dc microgrid PLC channel is examined. It is shown in this paper that while Lyapunov asymptotic stability is maintained on the dc bus, increasing CPL on the microgrid causes the dc microgrid PLC channel to experience growing signal distortion.

DC microgrid is gaining attention of researcher due to their higher efficiency, more reliability and easy integration with renewable sources. Along with all advantages, it also creates design challenges for the researcher. To address one of the challenge, in this paper a small-signal mathematical modeling of an islanded dc microgrid has been derived in closed-loop and the effect of controller gain on the microgrid stability has been studied for constant power load. The eigenvalue analysis has been carried out for the tuning of controller, which ensures the stable operation. An islanded dc microgrid is simulated using Matlab/Simulink and validated through analysis.

This paper studies stability analysis of DC microgrids with uncertain constant power loads (CPLs). It is well known that CPLs have negative impedance effects, which may cause instability in a DC microgrid. Existing works often study the stability around a given equilibrium based on some nominal values of CPLs. However, in real applications, the equilibrium of a DC microgrid depends on the loading condition that often changes over time. Different from many previous results, this paper develops a framework that can analyze the DC microgrid stability for a given range of CPLs. The problem is formulated as a robust stability problem of a polytopic uncertain linear system. By exploiting the structure of the problem, we derive a set of sufficient conditions that can guarantee robust stability. The conditions can be efficiently checked by solving a convex optimization problem in polynomial time. The effectiveness and non-conservativeness of the proposed framework are demonstrated using a simulation example.

DC microgrid consists of cascaded power converters in which the constant power load behaviour of point-of-load converters poses challenging stability issues even if individual converters are stable. In this paper, a robust sliding mode controller has been proposed for DC/DC bidirectional buck-boost converter interfacing storage unit in an islanded DC microgrid environment. The controller is designed to ensure DC bus voltage regulation in the presence of renewable energy source and predominantly constant power loads. The performance of the proposed controller is validated through real-time simulation conducted using OPAL-RT® Digital Simulator. The controller ensures DC bus voltage regulation within tight limits and is robust with respect to wide variations in the renewable energy source power and the load.