• Energy Research

This paper investigates the problem of dynamic stabilization of dc microgrids (MGs) through a robust non-fragile fuzzy control synthesis of power buffer. The suggested robust fuzzy controller is designed to quickly stabilize the MGs by circulating the power between the dc link and an energy storage system (ESS). By employing the exponential stability analysis and Takagi–Sugeno fuzzy modeling, sufficient controller design conditions are derived in terms of linear matrix inequalities, which bring about a simple, systematic, and effective controller. The proposed approach is resilient against the uncertainties of the dc MG and ESS parameters. To show the merits of the proposed approach, it is applied to a dc MG that feeds one constant power load. It is shown that the proposed approach is more robust against system and controller uncertainties compared to the existing results. Finally, experimental results are then presented that show the transient performance improvement of the closed-loop system compared to the state-of-the-art methods.

This article classifies, describes, and critically compares different modeling techniques and control methods for dual-active-bridge (DAB) dc–dc converters and provides explicit guidance about the DAB controller design to practicing engineers and researchers. First, available modeling methods for DAB including reduced-order model, generalized average model, and discrete-time model are classified and quantitatively compared using simulation results. Based on this comparison, recommendations for suitable DAB modeling method are given. Then, we comprehensively review the available control methods including feedback-only control, linearization control, feedforward plus feedback, disturbance-observer-based control, feedforward current control, model predictive current control, sliding mode control, and moving discretized control set model predictive control. Frequency responses of the closed-loop control-to-output and output impedance are selected as the metrics of the ability in voltage tracking and the load disturbance rejection performance. The frequency response plots of the closed-loop control-to-output transfer function and output impedance of each control method are theoretically derived or swept using simulation software PLECS and MATLAB. Based on these plots, remarks on each control method are drawn. Some practical control issues for DAB including dead-time effect, phase drift, and dc magnetic flux bias are also reviewed. This article is accompanied by PLECS simulation files of the reviewed control methods.

Abstract In today's ecosystem of energy management, the contribution of Internet of Things (IoT) to smart grids has acquired immense potential due to its multi-faceted advantages in various fields. IoT paves a way to associate and virtually control everything in almost every domain of society. Conversely, the smart grid framework attracted the attention of the universal research community and the idea of merging IoT with smart grid together demonstrates enormous growth potential. This review paper highlights the most significant research works that focus on applying IoT to smart grids. This work also addresses many innovative approaches used in IoT and smart grids along with their respective applications in various fields. The objective of this work is to benefit scientists and new entrants in the field of IoT and smart grids opens up awareness for new interdisciplinary research.

In this paper, a complete small signal model of two networked microgrids (NMGs) is provided, which can be used in the stability analysis, stability margin derivation and controller design. This model is validated by comparing it with the simulated NMGs using the Prony analysis. In this method, the modes, calculated by eigenvalue analysis and contributing to a particular state variable, are identified using the participation matrix and compared with the natural frequencies of its waveform. The state variable waveform is locally measured from the simulated NMGs in the SimPowerSystems environment of MATLAB and its natural frequencies are calculated using Prony analysis. It is concluded that Prony analysis estimates the natural frequencies well and there is a good similarity between them and the calculated modes, which shows the modeling validation.

In this work, we propose an effective and simple control approach for islanded DC microgrids that allows each distributed generator (DG) to achieve accurate voltage regulation and power-sharing. An improved dynamic consensus protocol, which is robust to measurement noise and states initialization, is employed to enable each agent to locally calculate the average bus voltage with a sparse cyber network. On this basis, we propose a cooperative controller that merges the voltage regulation and power-sharing objectives in a unified fashion. The proposed approach only uses neighbors’ voltage information to regulates the average bus voltage to its nominal value while maintaining proportional power-sharing or optimal power dispatch. This significantly simplifies its implementation and reduces the communication bandwidth requirement. A global model of the DC microgrid considering the cyber network is established in the form of a state-space-model, where the reference voltage vector corresponds to the input and the average bus voltage vector denotes the state. Then, the input-to-state stability analysis is carried out. To the end, comprehensive hardware-in-the-loop (HiL) tests are conducted to validate the effectiveness of the proposed control strategy. The proposed control strategy exhibits plug-and-play capability, and it is resilient to message update rate and communication failure.

This article presents the modeling and verification of supervisory energy-management systems (EMSs) for microgrids using timed automata (TA) and a formal verification approach. The EMS plays an essential role in managing the power flow among different components in the microgrid system for its safe and reliable operation. The modeling of the EMS is based on predefined invariants with allowable and nonallowable operating modes, which are the conditions that do not change over time. The failure of invariants could have severe effects on microgrid system functionality, which highlights the importance of verification during the initial stage of EMS design. Conventional approaches, such as simulation and/or experimental verification, require manual checking and skilled professional knowledge to check EMS design correctness. Also, there may be a corner case that could lead to system failure that goes unidentified by manual analysis.

By day-to-day improvement in a microgrid (MG) control, frequency regulation in the shipboard alternating current (ac) MGs has received much interest in the past decade. The shipboard MGs involve renewable energy sources (RESs) that are unable to produce reliable and constant energy. This important fact vividly demonstrates the requirement of modern frequency regulation techniques. This article proposes a novel dynamic output feedback controller (DOFC) for load frequency control (LFC) in a sample shipboard MG. The considered ac MG involves fuel cell, gas turbine, and diesel generator as the controllable power generators; photovoltaic array and sea wave energy converter as the renewable energy sources; and batteries and flywheels as the storage units. The existing approaches almost exploit linearization for solving the problem, which imposes restrictions on the problem and raises conservative constraints resulting in shrinking the solution space. This article suggests a simple approach that effectively reduces such limitations through the formulation of sufficient conditions on the controller design in the form of bilinear matrix inequalities (BMIs). This consequences in a more exact solution compared to the previous methods. To show the merits of the developed approach, OPAL real-time (RT) simulations are executed, and the results are compared to the other state-of-the-art-methods that prove the efficacy of the suggested approach. Also, the results of our proposed method (DOFC; $n=2$ and $n=3$ ) are compared to the typical $\mathrm {H}_{\infty }$ optimization, ${\mu }$ -synthesis, fuzzy type-1, and intelligent-PI methods. The comparisons between norms of the frequency deviation verify the efficacy of the proposed controller in this article.