Decentralized Control Strategy for a Stand-Alone DC Microgrid based on Voltage Droop and Virtual Impedance

Recently, direct current (DC) microgrids have gained more attention over alternating current (AC) microgrids due to the increasing use of DC power sources, energy storage systems and DC loads. However, efficient management of these microgrids and their seamless integration within smart and energy efficient buildings are required. This paper introduces an energy management strategy for a DC microgrid, which is composed of a photovoltaic module as the main source, an energy storage system (battery) and a critical DC load. The designed MG includes a DC-DC boost converter to allow the PV module to operate in MPPT (Maximum Power Point Tracking) mode or in LPM (Limited Power Mode). Furthermore, the system uses a DC-DC bidirectional converter in order to interface the battery with the DC bus. The proposed control strategy manages the power flow among different components of the microgrid. It takes the battery lifetime into consideration by applying constraints to its charging/discharging currents and state-of-charge (SoC). The proposed system is simple and efficient in supplying DC loads, since as it’s not using complex algorithms either for MPPT or for energy management. The studied DC microgrid is designed and modeled using Matlab/Simulink software. The load demand is satisfied while ensuring good performance and stability of the system. The controller design, analysis, and simulation validation results are presented and discussed under various operating modes.

The direct current (DC) systems have outstanding advantages compared to the alternating current (AC), especially when it comes to renewable energy resources (RER) and microgrids (MGs). Therefore, the DC microgrid (DCMG) has become popular and drawn the attention of researchers. Due to the integration of different power sources in the single DC bus, including solar photovoltaics (PV), wind farms, diesel generators, and energy storage systems, maintaining stable bus voltage requires a complicated control system to ensure a fast-decision-making procedure. This paper presents an energy management strategy for the DCMG using a fuzzy logic-based controller. The proposed DCMG uses a hybrid energy storage system (HESS) for energy balancing and a diesel generator as a backup. The proposed strategy uses generation and loads demand and battery state of charge (SoC) to control the power flow within the MG. The energy management system keeps the SoC in a suitable range to increase the battery life. By controlling the charging and discharging of the HESS, the proposed method has a fast response to the load variation and RER intermittency to prevent the fluctuation of the voltage level of the DC bus and keep it constant. The obtained results validate the efficacy of the proposed fuzzy logic controller.

High-performance power conversion needs are becoming more and more important for microgrid applications. In actuality, many contemporary DC distribution systems use isolated bidirectional dc-dc converters. Hence, in this paper, an Improved Adaptive Network-based Fuzzy Inference System (IANFIS)is developed to control the output power of the components and reduce the variation among the consumption and generation of the power while managing a constant DC bus voltage. This work proposes a power management control strategy that ensures the power balance of a stand-alone DC microgrid where DAB converters link the battery energy storage (BES) unit and the renewable energy source (RES). The generation side, or photovoltaic (PV) system and BES, is coupled to the storage systems and renewable energy sources. Furthermore, a DC microgrid is connected to the load demand. The load demand is compensated with the help of the storage and generation systems with the help of a dual active bridge converter. The DAB is connected with the dual DC microgrid system for managing power flow among the two DC microgrids. This dual active bridge converter is utilized to balance the power among Dual DC microgrids. The proposed methodology is developed to manage the power among generation and load demand management. The proposed method is evaluated on a dual active bridge converter connected microgrid system with the components of PV and BESS respectively.

With the rapid development of renewable energy technologies, islanded DC microgrids have received extensive attention in the field of distributed power generation due to their plug-and-play, flexible operation modes and convenient power conversion, and are likely to be one of the mainstream structures of microgrids in the future. The islanded DC microgrid contains multiple distributed power generation units. The battery energy storage system (BESS) is the main controlled unit used to smooth power fluctuations. The main parameter of concern is the state of charge (SOC). In order to maintain the stability of the microgrid, this paper takes the islanded DC microgrid as the research object and designs a control strategy based on the SOC of the BESS. Additionally, in the control strategy, the BESS’s energy balance control strategy and the microgrid’s operation control strategy are emphatically designed. The designed BESS control strategy adjusts the droop coefficient in real time according to the SOC of the battery energy storage unit (BESU), and controls the charge and discharge power of the BESU to achieve the SOC balance among the BESUs. The microgrid operation control strategy takes the energy storage system (ESS) as the main controlled unit to suppress power fluctuations, and distributes the power of distributed power sources according to the SOC of the BESS to achieve power balance in the microgrid, and control the DC bus voltage fluctuation deviation within 4.5%.

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.

The DC microgrid with photovoltaic and energy storage system has become a prevailing trend for new energy. However, the whole system involves a variety of power electronic converter interactions, so it is necessary to conduct system stability analysis. Firstly, the topology and control strategies of the DC microgrid with photovoltaic and energy storage system are introduced, including photovoltaic power generation system and its control, energy storage system and its control, and grid and grid-side converter topology and its control. Secondly, the impedance or admittance of these three units are modeled separately. Next, each unit is equivalent into the corresponding voltage source system or current source system, and the impedance proportion of the DC microgrid with photovoltaic and energy storage system is obtained. Then based on the Nyquist stability criterion, the obtained impedance proportion is used to analyze the impacts of the proportional parameters of the voltage loop of the grid-side converter, the control parameters of the current loop of the energy storage system, as well as the capacity of the energy storage system and the charging and discharging states of the energy storage on the stability of the DC microgrid with photovoltaic and energy storage system.

Energy management in DC microgrid with an efficient voltage compensation mechanism

In this study, a DC microgrid is proposed for a typical school load demand for the Roorkee, India location where the major load demand is electrical loads such as lighting, fan, RO water purifier. The other loads are the auxiliary electrical power supplies of the solar thermal unit which is operational at the site and used for the mid-day meal application. In the DC microgrid, solar photovoltaic (PV) is considered as the main power generator whereas battery energy storage medium is considered as the backup power source. PV power can be utilized, first to meet the required load demand and the excess power is used to charge the battery bank. In case, PV power is in deficit then the battery bank is discharged to meet the load demand uninterruptedly. In this study; firstly, a techno-economic analysis of off-grid DC microgrid with lead-acid battery energy storage has been performed using a hybrid optimization model for electric renewables (HOMER) simulation tool. Secondly, the proposed DC microgrid has also been implemented at a reduced scale at the selected site location. It is found that such type of DC microgrid is self-sufficient and efficient to meet the load demand uninterruptedly.

This paper deals with the model predictive current control of a three‐level bidirectional buck‐boost converter for a battery energy storage system in a bi‐polar direct current (DC) microgrid. It comprises a solar photovoltaic system, a wind energy system, a battery and DC loads. The proposed control scheme provides voltage balance and voltage regulation at the bi‐polar DC link during dynamic operating conditions, such as variations in solar irradiance, wind velocity and load. Predictive current control utilises the converter's discrete behaviour to identify the suitable switching states that minimise the cost function. Furthermore, bidirectional power flow capabilities allow the connection of energy storage devices, such as batteries and ultra‐capacitors, to the bi‐polar DC microgrid. The proposed system is verified through simulations and validated on a lab‐scale prototype. The results have been found satisfactory with respect to steady‐state error, peak overshoot, and settling time.

DC microgrids, which combine multiple renewable energy sources, have gained attention due to their advantages in terms of cost, efficiency, and reliability, particularly in remote areas. However, voltage stability, efficient energy management, and the degradation of storage device lifespan due to frequent load and source fluctuations are among the main practical challenges faced by DC microgrids. This paper presents an advanced approach to energy management within DC microgrids, addressing these challenges by incorporating real‐world weather data and community load demands. Weather data, including temperature, solar radiation, and wind speed, are sourced from reputable repositories such as SWERA, NASA, and local meteorological agencies. The economic viability of solar, wind, and energy storage systems is meticulously evaluated using HOMER Pro software, aiding in the identification of viable energy sources. Once optimized energy resources, energy storage solutions, and load demands are identified, a systematic approach is taken. This involves the selection, mathematical modeling, and sizing of converter components. To ensure the efficiency of the intended DC microgrid, control and energy management algorithms are proposed. The proposed energy management system adopts a coordinated approach, seamlessly integrating droop control, adaptive filter‐based method, and fuzzy logic control techniques. To evaluate the efficacy of the proposed system, two primary case studies are simulated using MATLAB/Simulink, employing authentic weather and community load data. The results unequivocally demonstrate that the proposed system exhibits heightened stability, efficiency, and reliability when compared to previously proposed methods. The maximum voltage overshot and voltage dip are 2.8 V and 1.6 V, respectively. The settling time of overshot and voltage drop is 0.07 S and 0.04 S, respectively. This superior voltage regulation achieved by the proposed method is a pivotal contributor to overall system stability and reliability.

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.

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 the low-voltage (LV) ac microgrids (MGs), with a relatively high R/X ratio, virtual impedance is usually adopted to improve the performance of droop control applied to distributed generators (DGs). At the same time, LV dc MG using virtual impedance as droop control is emerging without adequate power flow studies. In this paper, power flow analyses for both ac and dc MGs are formulated and implemented. The mathematical models for both types of MGs considering the concept of virtual impedance are used to be in conformity with the practical control of the DGs. As a result, calculation accuracy is improved for both ac and dc MG power flow analyses, comparing with previous methods without considering virtual impedance. Case studies are conducted to verify the proposed power flow analyses in terms of convergence and accuracy. Investigation of the impact to the system of internal control parameters adopted by DGs is also conducted by using proposed method.

A novel distributed secondary layer control strategy based on average consensus and fractional‐order proportional‐integral (FOPI) local controllers is proposed for the regulation of the bus voltages and energy level balancing of the energy storage systems (ESSs) in DC microgrids. The distributed consensus protocol works based on an undirected sparse communication network. Fractional‐order local controllers increase the degree of freedom in the tuning of closed‐loop controllers, which is required for DC microgrids with high order dynamics. Therefore, here, FOPI local controllers are proposed for enhanced energy balancing of ESSs and improved regulation of the bus voltages across the microgrid. The proposed control strategy operates in both islanded and grid‐connected modes of a DC microgrid. In both modes, the average voltage of the microgrid converges to the microgrid desired reference voltage. The charging/discharging of ESSs is controlled independent of the microgrid operating mode to maintain a balanced energy level. The performance of the proposed distributed control strategy is validated in a 38‐ V DC microgrid case study, simulated by Simulink real‐time desktop, consisting of 10 buses and a photovoltaic renewable energy source.

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.