Multiagent Supervisory Control for Power Management in DC Microgrids

This paper investigates optimal power management in dc microgrids, with its applications to dc dual-source trolleybus systems. High mobility of buses and their impact on power supply networks introduce challenging power management issues. This paper incorporates line power losses in power management strategies and introduces a new distributed optimal power management methodology. A multi-objective optimization model is developed. Using only neighborhood information exchange among feeder lines in the network, the new consensus-type control accommodates both feeder current allocation and power loss reduction with fast convergence. One critical finding of this paper is that our local recursive optimization algorithms achieve the global optimal solution asymptotically. Under random noise on information exchange, convergence and optimality of the proposed method are established rigorously. The power system configurations of the Beijing dual-source trolleybus system are used for simulation case studies on the new power management methods. Feasibility, accuracy, and comparison with global optimization results are demonstrated.

A DC microgrid with DC bus signaling (DBS) for power management offers a promising and cost-effective solution for reliable electricity access in rural and remote communities, particularly in developing nations. In this article, a three-layer modularized model of a microgrid is presented, with emphasis on the “Basic DC Microgrid Model” (Layer 1), which ensures effective power management in the microgrid at all times. Through the framework of the Layer 1 model, various energy management scenarios (EMSes) can be implemented, by varying the voltage regulation priorities of the entities. This allows us to achieve different system objectives such as reduced battery requirement or less dependence on the AC Grid. Two of the EMSes are discussed, implemented, and examined through both digital simulations and experimental tests on a laboratory prototype. The results show that the DBS scheme achieves real-time power management in a DC microgrid and that different EMSes can be easily implemented to realize varied system-level objectives.

An adaptive droop control with constant voltage regulation is proposed for the power and voltage management of a DC microgrid (DCMG) with multiple power sources, such as a utility grid (UG), a distributed generator (DG), an energy storage system (ESS), and an electric vehicle (EV). In the proposed scheme, the droop characteristics for the UG, ESS, and EV are adaptively changed according to electricity price conditions and state-of-charge (SOC) levels in order to optimize the DCMG operation flexibility as well as electricity cost. The proposed control method not only ensures the power-sharing of DCMG reliably without the use of a communication link, but also regulates the DC bus voltage stably at the nominal value. To achieve this, the proposed scheme consists of primary control and secondary control. The primary control is used to achieve power-sharing in the decentralized DCMG, while the secondary control is used to overcome the disadvantage of conventional droop control, i.e., to remove DC bus voltage deviations. Decentralized power management is also presented to enhance the DCMG system reliability in the presence of uncertainties such as DG generation power, the ESS and EV SOC levels, the grid and EV availabilities, the load demand, and electricity price conditions. The effectiveness of the proposed scheme is demonstrated in a comprehensive simulation and experiment under various conditions. The test results clearly confirm the control flexibility and overall performance of the proposed control scheme for decentralized DCMG system.

In this paper, a nonlinear decentralized double‐integral sliding mode controller (DI‐SMC) is designed along with an energy management system (EMS) for the DC microgrid (DCMG). This DCMG includes having a hybrid energy storage system (HESS) that incorporates a battery energy storage system (BESS) and supercapacitor energy storage system (SCESS) while the load demand is met through the power generated from solar photovoltaic (SPV) units. First, dynamical models of each subsystem of DCMGs such as the SPV system, BESS, and SCESS are developed to capture highly nonlinear behaviors of DCMGs under various operating conditions. The proposed nonlinear DI‐SMC is then designed for each power unit in DCMGs to ensure the desired voltage level at the common DC‐bus and appropriate power dispatch of different components to fulfill the load requirement of the DCMG. On the other hand, an energy management system (EMS) is designed to determine the set point for the controller with an aim of ensuring the power balance within DCMGs under various operating conditions where the overall stability is assessed using the Lyapunov theory. Simulation studies along with the processor‐in‐loop validation, including a comparative study with a proportional‐integral (PI) controller, verify the applicability and effectiveness of the EMS‐based DI‐SMC under different operating conditions of the DCMG.

A hierarchical power management scheme is proposed in this paper for a typical DC Microgrid. Different from other Microgrids, the DC Microgrid can interface to the distribution system by Solid-State transformer (SST). The hierarchical power management strategy includes three control levels: 1) primary control for DC Microgrid to implement distributed operation 2) secondary control for the DC Microgrid bus voltage recovery to achieve seamless mode switch 3) tertiary control to manage the battery charge and discharge. The DC Microgrid can operate in islanding mode, including the individual control for distributed renewable energy source (DRER) and distributed energy storage device (DESD). In addition, the DC microgrid can operate in SST-enabled mode to interface to the distribution system. The DC Micorgrid can seamlessly switch between islanding mode and SST-enable mode. The consideration of state of charge (SOC) for battery is also involved into the tertiary control. To this end, a lab test-bed is constructed to verify the system performance. Lastly, several typical case studies are carried out and the experimental results verify the proposed power management strategy.

Energy management in DC microgrid with an efficient voltage compensation mechanism

This study is focused on two areas: the design of a Battery Energy Storage System (BESS) for a grid-connected DC Microgrid and the power management of that microgrid. The power management is performed by a Microgrid Central Controller (MGCC). A Microgrid operator provides daily information to the MGCC about the photovoltaic generation profile, the load demand profile, and the real-time prices of the electricity in order to plan the power interchange between the BESS and the main grid, establishing the desired state of charge (SOC) of the batteries at any time. The main goals of the power management strategy under study are to minimize the cost of the electricity that is imported from the grid and to maximize battery life by means of an adequate charging procedure, which sets the charging rate as a function of the MG state. Experimental and simulation results in many realistic scenarios demonstrate that the proposed methodology achieves a proper power management of the DC microgrid.

Instability problems caused by constant power loads as a result of the negative impedance effect are dealt with in this article. A comprehensive nonlinear model of a single-bus DC microgrid is developed, and a model predictive controller is designed to enhance voltage stability and optimize power management based on the developed model. Conventional control layers are replaced by a simplified optimal controller in the proposed approach in the presence of various load types, including constant power loads. Furthermore, the model and control strategy are extended to the multi-bus DC microgrid. Extensive stability analysis, including root locus methods and time-domain simulation, has been conducted in MATLAB/SIMULINK. The results confirm the effectiveness of the designed controller in maintaining system stability and improving performance under different operating conditions.

A novel distributed power management scheme is proposed in this paper for a DC microgrid system, which is enabled by Solid-State transformer (SST). The proposed system includes distributed renewable energy resource (DRER) and distributed energy storage device (DESD). The proposed distributed control algorithm, which only relies on the local information and guarantees full utilization of each module in the system based on their characteristics, is applied to both SST and DC microgrid. To this end, a simulation platform is developed in MATLAB/Simulink, in which Photovoltaic (PV), fuel cell and battery are selected as the typical DRERs and DESD, respectively. Lastly, several typical case studies are carried out and the simulation results verify the proposed distributed power management.

DC microgrids can be created by integrating renewable energy resources at the distribution level. There are numerous advantages to using a grid-connected microgrid to meet the rising electricity demand. An isolated DC microgrid with solar PV arrays, wind turbines, and battery energy storage systems is shown to be connected to the grid in this study. The AC/DC bi-directional converter linked to the DC microgrid serves as the primary control for the Master controller. The PWM signal generated by the transformations is used to start and change the converter's mode of operation. Batteries can be used as a slave to the grid's power management in a DC microgrid. The case study of Islanding and Grid-connected are analyzed and simulated using MATLAB/Simulink. The study's findings offer some preliminary pointers for achieving long-term well-being. In order to achieve the best possible power system goals, a variety of factors may need to be carefully considered.

In this chapter, the author presents the operation and power management of the hydrogen storage-based smart DC microgrid (DCMG). In this microgrid, several renewable distributed generations (DGs) such as wind turbine, solar photovoltaic system, solid oxide fuel cell (SOFC), and battery energy storage system are interconnected together and to the various DC and AC loads to form a ring-type low voltage distribution network. An additional storage as Hydrogen storage system has been connected to the dc microgrid for balancing the power at all times in the DCMG, under islanded mode operation, for all practical cases. An architecture of the hydrogen storage-based DC microgrid is suggested mainly for the remote rural area. For the regeneration of the electricity from the stored hydrogen, a SOFC DG system is also used in the proposed DCMG. A control technique is also developed for the operation of the hydrogen storage-based DCMG. The proposed DCMG system provides a reliable and high-quality power supply and will supply the power to all loads (both DC and AC) simultaneously.

Microgrids are receiving tremendous attention due to increasing need to integrate Distributed Generations (DG) and to provide reliable power to critical loads. Proper power management in microgrid is required to regulate the system voltage and frequency, maintain power quality, and manage DGs. A microgrid system has been studied in this paper, which includes two natural gas generators, an energy storage device, solar PV, and a wind turbine. The DGs are modeled in details using PSCAD software and the practical constraints of the components are considered. The Virtual Droop Control (VDC) method for microgrid power management is proposed and described in details. The proposed technique has been applied to adjust the active and reactive power of each component in order to manage the system. Unit commitment algorithm has also been implemented to improve the system efficiency.

This comprehensive review critically analyses the complex correlation between DC microgrids and the incorporation of Distributed Generation (DG). It offers a full evaluation of fundamental principles, advanced control strategies, technology advancements, and practical implementations in real-world scenarios. This research examines the ability of Direct Current (DC) microgrids to effectively integrate and optimize various DG sources within the context of a paradigm shift towards decentralized energy solutions. The paper critically examines the obstacles and opportunities associated with renewable energy systems and different DG technologies. It provides essential insights for researchers, engineers, and politicians who are involved in the complex process of integrating distributed energy into existing systems. This review serves as a crucial resource that contributes to the understanding of DG in DC microgrids. It plays a significant role in developing conversations surrounding energy solutions that are both resilient and sustainable. This paper not only discusses the difficulties related to the integration of DG, but also emphasizes practical examples that demonstrate the flexibility and effectiveness of DC microgrid designs. This study serves as a crucial resource for stakeholders who aim to use the potential of DC microgrids, since it encompasses a comprehensive analysis of power electronics, energy storage, and sophisticated control systems. By combining critical evaluation with practical implementation, this review offers valuable insights and guidance in the field. The complete investigation plays a significant role in advancing the integration of DG, which is essential for creating a resilient and sustainable energy environment. It provides basic information that is needed for achieving effective integration. This review paper provides a comprehensive examination of the integration of DG within DC microgrids. From laying the groundwork with fundamental principles to scrutinizing challenges, technological advancements, and practical applications, this review aims to offer a holistic understanding of the dynamic landscape where DC microgrids intersect with distributed energy generation.

Direct Current (DC) microgrids are expected to become larger due to the rapid growth of DC energy sources and power loads. As the scale of the system expends, the importance of voltage control will be increased to operate power systems stably. Many studies have been performed on voltage control methods in a DC microgrid, but most of them focused only on a small scale microgrid, such as a building microgrid. Therefore, a new control method is needed for a middle or large scale DC microgrid. This paper analyzes voltage drop problems in a large DC microgrid and proposes a cooperative voltage control scheme with a distributed generator (DG) and a grid connected converter (GCC). For the voltage control with DGs, their location and capacity should be considered for economic operation in the systems. Accordingly, an optimal DG allocation algorithm is proposed to minimize the capacity of a DG for voltage control in DC microgrids. The proposed methods are verified with typical load types by a simulation using MATLAB and PSCAD/EMTDC.

This paper proposes a hierarchical active power management strategy for a medium voltage (MV) islanded microgrid including a multihybrid power conversion system (MHPCS). To guarantee excellent power management, a modular power conversion system is realized by parallel connection of small MHPCS units. The hybrid system includes fuel cells (FC) as main and supercapacitors (SC) as complementary power sources. The SC energy storage compensates the slow transient response of the FC stack and supports the FC to meet the grid power demand. The proposed control strategy of the MHPCS comprises three control loops; dc-link voltage controller, power management controller, and load current sharing controller. Each distributed generation (DG) unit uses an adaptive proportional resonance (PR) controller for regulating the load voltage, and a droop control strategy for average power sharing among the DG units. The performance of the proposed control strategy is verified by using digital time-domain simulation studies in the PSCAD/EMTDC software environment.