Islanded DC Microgrid Research Articles

Distributed adaptive power management for medium voltage ship power systems

Systems are being developed for power distribution on future navy ships to effectively incorporate advanced electrical systems requiring DC power. These islanded DC microgrids provide new challenges to the management of power flow throughout the system, and thus require advanced controls to accurately regulate and stabilise the systems during changing operational conditions. Therefore, adaptive droop control is proposed as a power management layer for these maritime DC microgrids. This paper reports on a method that uses adaptation of the controller parameters to account for uncertainty and changes in the system in order to accurately regulate the power sharing among distributed generation sources and to stabilise the bus voltage of the system. The proposed method is applied to a virtual prototype of a medium voltage direct current (MVDC) ship power system and demonstrated through notional operational scenarios to test the effectiveness of the control algorithm utilising controller hardware in the loop (CHIL) experimentation.

Logarithmic droop‐based decentralized control of parallel converters for accurate current sharing in islanded DC microgrid applications

Remarkable progress in distributed power generation invigorated research into DC microgrids using a controllable DC–DC converter contingent to the functionalities therein. The study explores the circulating current issue in a parallel-connected DC–DC converter and its associated current-sharing capability. Despite, the conventional droop being a promising solution with less control complexity, the current sharing is achieved at an expense of voltage drop. The prime objective of this research work is to design a control strategy that guarantees a minimized circulating current with proper current sharing for a parallel-operated DC–DC converter. This paper puts forth a dual reference-based control to alleviate the droop and load effects of the system. The primary reference is generated by considering the effect of a marginal change in the input power of the converters. The virtual resistance-based droop technique utilizes the prime reference for secondary droop reference generation. A current sharing algorithm is designed to assimilate adaptability to the scheme running under a variable line and load parameters. The comprehensive approach to the proposed control strategy has the advantages of improved current sharing and voltage regulation. A parallel DC–DC converter with the proposed control mechanism was investigated using MATLAB/Simulink and validated experimentally.

Robust Performance Satisfaction of DC Microgrids Using a Decentralized Optimal Voltage Control Strategy

In this article, a decentralized scalable voltage control approach for islanded dc microgrids with a general structure is proposed. The microgrid system under study comprises several distributed generation (DG) units, every one containing an uncertain local ZIP [constant impedance (Z), constant current (I), and constant power (P)] load. We propose a voltage control strategy that ensures robust desired performance of the closed-loop islanded dc microgrid in addition to the robust stability under different uncertainty sources, including uncertain ZIP loads, topological changes, and plug-and-play functionality of DGs. The presented approach does not impose any restrictions on the dynamics of the distribution lines connecting different DG units. In the proposed control scheme, each local controller is the solution of a single convex optimization problem, which leads to the optimal performance of the dc microgrid. At first, an LTI state-space model with polytopic uncertainty is developed for islanded dc microgrid with different uncertainty sources. Then, a robust dynamic output-feedback-based controller with <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${{\boldsymbol{H}}_\infty }$</tex-math></inline-formula> performance criterion is proposed for the satisfaction of all control objectives. The final obtained problem is turned into an LMI-based optimization problem. Different scenarios are simulated in MATLAB to affirm the feasibility and efficiency of the proposed control technique in the dc microgrids.

An optimised state‐of‐charge balance control strategy for distributed energy storage units in islanded DC microgrid

An optimised state‐of‐charge balance control strategy for distributed energy storage units in islanded DC microgrid

Coordinated control method of multiple hybrid energy storage systems based on distributed event-triggered mechanism

An islanded DC microgrid with multiple hybrid energy storage systems is the object of this research, and a hierarchical coordinated control method of hybrid energy storage systems based on an event-triggered mechanism is proposed. The local layer adopts a virtual-resistance droop control and conducts the power distribution of a battery and a supercapacitor using a low-pass filter. Control strategies based on the state of charge are proposed to achieve coordinated and safe operation between hybrid energy storage systems. The distributed control layer uses a sparse communication network to regulate the average voltage and the proportional current of each hybrid energy storage system to improve the problems arising from a large bus voltage deviation and poor power sharing accuracy caused by virtual and line resistances. Based on this research, a Zeno-free event-triggered control method is proposed. The detailed derivation and proof process of the method is introduced using Lyapunov stability theory. This method can achieve similar control performance as time-triggered, but with fewer communication traffic. By setting prejudgment thresholds of the triggering function, the communication traffic is further reduced during the steady state of the system. Finally, simulations studies are conducted to demonstrate the effectiveness and robustness of the proposed control method in an islanded DC microgrid.

Integrated Control and Protection Architecture for Islanded PV-Battery DC Microgrids: Design, Analysis and Experimental Verification

Direct current (dc) microgrids have gained significant interest in research due to dc generation/storage technologies—such as photovoltaics (PV) and batteries—increasing performance and reducing in cost. However, proper protection and control systems are critical in order to make dc microgrids feasible. This paper aims to propose a novel integrated control and protection scheme by using the state-dependent Riccati equation (SDRE) method for PV-battery based islanded dc microgrids. The dc microgrid under study consists of photovoltaic (PV) generation, a battery energy storage system (BESS), a capacitor bank and a dc load. The aims of this study are fast fault detection and voltage control of the dc load bus. To do so, the SDRE observer-controller—a nonlinear mathematical model—is employed to model the operation of the dc microgrid. Simulation results show that the proposed SDRE method is effective for fault detection and robust against external disturbances, resulting in it being capable of controlling the dc load bus voltage during disturbances. Finally, the dc microgrid and its proposed protection scheme are implemented in an experimental testbed prototype to verify the fault detection algorithm feasibility. The experimental results indicate that the SDRE scheme can effectively detect faults in a few milliseconds.

A Power Sharing Strategy for Islanded DC Microgrid with Unmatched Line Impedance and Local Load

The novel load power sharing control strategy is proposed for parallel-connected distributed generation units of islanded DC microgrid considering both unmatched line impedance and local load. Because the output voltage of DGs may be different, so the accurate load power sharing cannot be assured only by using conventional droop control method. Therefore, the improved droop control based on virtual voltage is designed to replace the actual output voltage, which can reduce the voltage deviation and achieve the accurate load power sharing among parallel-connected DGs in proportion to their rated power. Meanwhile, the droop coefficient setting principle is also designed to avoid large DC bus voltage drop. Furthermore, the stability analysis can be added to guarantee the stability operation of DC microgrid theoretically. The proposed control strategy may be realized locally, which need not to change the control scheme even when DGs and loads are increased or decreased. Finally, the effectiveness of the designed control scheme can be verified through Matlab/Simulink software, at the same time, the experimental results are carried out on real-time digital simulation platform.

A Unified Distributed Cooperative Control of DC Microgrids Using Consensus Protocol

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.

Hierarchical Control in Islanded DC Microgrids With Flexible Structures

Hierarchical architectures stacking primary, secondary, and tertiary layers are widely employed for the operation and control of islanded dc microgrids (dcmGs) composed of distribution generation units (DGUs), loads, and power lines. However, a comprehensive analysis of all the layers put together is often missing. In this work, we remedy this limitation by setting out a top-to-bottom hierarchical control architecture. Decentralized voltage controllers attached to DGUs form our primary layer. Governed by an MPC-based energy management system (EMS), our tertiary layer generates optimal power references and decision variables for DGUs. In particular, decision variables can turn DGUs on/off and select their operation modes. An intermediary secondary layer translates EMS power references into appropriate voltage signals required by the primary layer. More specifically, to provide a voltage solution, the secondary layer solves an optimization problem embedding power-flow equations shown to be always solvable. Since load voltages are not directly enforced, their uniqueness is necessary for DGUs to produce reference powers handed down by the EMS. To this aim, we deduce a novel uniqueness condition based only on local load parameters. Our control framework, besides being applicable for generic dcmG topologies, can accommodate topological changes caused by EMS commands. Its functioning is validated via simulations on a modified 16-bus dc system.

Multi-Time Scale Energy Management and Optimal Dispatch Scheme for Islanded DC Microgrid Operation

DC microgrid has outstanding advantages in accepting new energy generation system and DC load, etc. This paper takes theislandedDC microgrid as the research object, and proposes a multi-time scale optimization scheduling scheme for theislandedDC microgrid. On the basis of satisfying the power balance of the DC bus and considering the factors of economy and environmental protection, this scheme realizes the optimized operation of the DC micro-grid under the isolated island mode. The optimization scheme consists of two stages: day-ahead scheduling and intraday scheduling. According to the short-term forecast data in advance, the day-ahead dispatching takes economic and environmental protection as the target todispatch controllable unit. In this paper, intraday scheduling maintains the power of the battery energy storage and interruptible loads determined by day-ahead scheduling. Taking ultra-short-term prediction data as the premise, intraday scheduling takes the minimum deviation between the output power of controllable power supply and the corresponding value of day-ahead scheduling as the target to formulate scheduling scheme. Finally, an example is given to verify the feasibility of the optimized scheduling scheme by simulating the proposed program on MATLAB.

A Virtual Inertia and Damping Control to Suppress Voltage Oscillation in Islanded DC Microgrid

In this paper, a virtual inertia and damping control (VIDC) strategy is proposed to enable bidirectional DC (bi-DC) converter to dampen the voltage oscillation, using the energy stored in energy storage system (ESS) to emulate the inertia of DC microgrid (DC-MG) without modifications of system hardware. Both inertia part and damping part are modelled in the VIDC regulator, by analogizing with DC machine. Droop control is introduced to achieve multi-parallel operation of ESS. Further, its small signal model is established and the dynamic characteristic of the DC bus voltage during power fluctuation is analyzed. A 2nd-order equivalent model is introduced to simplify the parameters design. By analyzing the control performance indices, the VIDC parameters are optimized. At last, based on the principle of equivalent machine, an inertia matching method of the multi-parallel bi-DC converters is proposed. The simulation results verify that ESS, by acting as a synthetic inertia, can improve the voltage dynamic characteristics and stability in islanded DC-MG. Compared with other control methods, it has better control effect.

Modeling and Control of Islanded DC Microgrid Clusters With Hierarchical Event-Triggered Consensus Algorithm

This paper proposes a distributed hierarchical control framework for energy storage systems (ESSs) in DC microgrid clusters, which achieves voltage regulation and current sharing for ESSs in each microgrid as well as the whole microgrid cluster. The primary control stage adopts a droop controller which only requires local information while the secondary control stage provides correction terms for ESSs within microgrids. The tertiary control stage samples the pinned ESSs in different microgrids with low sampling rate to provide the voltage setpoint, which ensures global current sharing among microgrid cluster. The corresponding multilayered event-triggered consensus algorithm for clusters is proposed to reduce the communication cost generated by operation of the distributed controller. Both the control framework and the consensus algorithm can be extended for satisfying higher dimensional regulation needs. The controller is validated in a DC microgrid cluster through simulation under different scenarios, and the results illustrate the effectiveness of the proposed controller.

Energy management strategy with two degrees of freedom for hybrid energy storage systems in islanded DC microgrids

In this study, a novel energy management strategy (EMS) with two degrees of freedom is proposed for hybrid energy storage systems consisting of supercapacitor (SC) and battery in islanded microgrids. The proposal introduces two degrees of freedom including an adaptive high-pass filter cut-off frequency f c and a charge/discharge coefficient kb, according to the SC and battery state of charge (SOC), respectively. The f c regulates SC current in the transient process and the kb controls battery current in the steady-state. Therefore, appropriate power distribution that the SC suppresses the transient power fluctuations while the battery supports average power demand is realised, over-charging, and over-discharging are avoided and the current stress of the battery during the shut-down process is reduced. Moreover, three operation modes for isolated DC microgrids, comprising power-sharing mode, battery-only mode, and extreme mode are demonstrated. Hence, the DC microgrid can remain stable for the whole time, achieve seamless transitions from the power-sharing mode to the two others, and provide faster SOC recovery of the SC. The effectiveness of the proposed EMS is validated by experimental studies with a prototype of the simplified DC microgrid.

Effective Control and Management Scheme for Isolated and Grid Connected DC Microgrid

This article addresses a voltage control and energy management strategy of active distribution systems with a grid-connected dc microgrid as well as for an islanded dc microgrid with hybrid energy resources. In the islanded mode, a control and management strategy using a backup diesel generator (DG), a renewable energy source (RES), and an energy storage system plays a vital role in maintaining the microgrid bus voltages within the limits. However, operating backup diesel generator (DG) has its own challenges including startup delay, frequent switching, and uneven loading when operated along with a RES. Additionally, fuel efficiency and emission characteristics vary with loading since most of DGs are driven by constant-speed diesel engines. Hence, an exhaustive power management scheme (PMS) is proposed by utilizing the hybrid energy storage system. Real-time simulation and experimental validation of the proposed scheme are provided using a real-time digital simulator (RTDS) and a laboratory-scale prototype, respectively. Extreme scenarios including DG failure/scheduled maintenance, low power generation, and battery charge are analyzed in the islanded mode. Furthermore, a dc microgrid is connected to an IEEE active distribution system feeder to analyze control and management challenges for the grid connected mode with contribution from a microgrid and with no contribution from a microgrid. These scenarios resemble more realistic unbalanced utility grid conditions. A centralized optimization problem is formulated at an advanced distribution management system level to maintain all the node voltages within limits in the IEEE test system. RTDS is used to simulate dc microgrid connected with the IEEE test system and an optimization algorithm is implemented in MATLAB. Superior performance of the developed algorithms are demonstrated and validated for coordination between centralized optimization at ADMS and the microgrid energy management system.

Decentralized Optimal Stabilization of Active Loads in Islanded Microgrids

This article proposes a decentralized, online optimal feedback control strategy to optimally stabilize active loads in islanded DC microgrids (DCMGs). Each active load is modeled as a control affine dynamical system with an interconnected coupling term in the energy and admittance domain. Then the decentralized, constrained input of each active load is obtained online in the feedback form to minimize the infinite horizon quadratic state cost and non quadratic control effort while supplying the active load demand. The approximate dynamic programming (ADP) approach is employed to solve the feedback optimal control problem online by successive approximation of the value function via two linear in the parameter (LIP) neural networks (NNs). A concurrent reinforcement learning (RL) based method is introduced to update the unknown weights in the NN. The convergence of the unknown weights to a neighborhood of the optimal weights and the uniformly ultimately bounded stability of the system are analyzed by a Lyapunov direct method. Series of simulation results are presented to demonstrate the effectiveness and the applicability of the proposed concept.

A Novel Secondary Optimal Control for Multiple Battery Energy Storages in a DC Microgrid

The distributed controller consisting of a voltage controller and a power controller is commonly employed on the secondary control layer in the DC microgrid. In this paper, a novel optimal control based on the PI consensus algorithm is proposed for multiple battery energy storages (BESs) in an islanded DC microgrid. Compared with the conventional distributed voltage controller, the proposed scheme improves the system robustness to time delays. The steady-state analysis is conducted to verify that the proposed scheme can take effect in case of time delays. The impact of the secondary controller on the dynamics of the system under time delays is investigated by the eigenvalue analysis. Simulation results confirm that favorable power sharing and DC voltage regulation as well as robustness to time delays achieved by optimal control in an islanded microgrid with multiple BESs and constant power load (CPL).

Communication-Free Power Management Strategy for the Multiple DAB-Based Energy Storage System in Islanded DC Microgrid

Along with the development of the renewable energy, such as the photovoltaics and the wind turbine, the energy storage system (ESS) is becoming as a critical part for the renewable-based microgrids. In this article, dual-active-bridge (DAB) dc-dc converter with bidirectional power flowing ability, wide soft-switching range, and ultrafast dynamic characteristic is adopted for integrating multiple energy storage units (ESUs) for balancing the power flowing between the renewable energy and the loads in a islanded dc microgrids. For the multiple DAB-based ESS, a communication-free power management strategy is proposed in this article to maintain the dc-link voltage for the islanded dc microgrid, and high robustness of the dc-link voltage can be ensured when the output voltage of energy storage equipment, the load condition, and the power sharing performance of the ESS are changed. The proposed strategy also ensures seamless ESU plug-in or plug-out operations. Finally, the small-scale simulation model and experimental platform are both employed to verify the effectiveness of the proposed communication-free power management scheme.

A Novel Power Scheduling Mechanism for Islanded DC Microgrid Cluster

Extension of the main grid to remote areas is economically not feasible. To electrify remote areas, one of the best choices is to install Renewable Energy Sources (RES) as a distributed generation (DG) and thus form a microgrid (MG) in islanded (Stand-alone) mode. In islanded mode, the MG has no support from the national grid. Thus, the overloading of islanded DC MG can collapse DC bus voltage and cause fluctuation in the load. Therefore, the power sharing and the interconnection among the microgrid (MG) cluster are necessary for reliable operation. Many methods for power sharing also aim at minimizing circulating currents which cannot be avoided when every MG feeds their load locally. Therefore, the proper power balancing among generation, loads, and in between MG cluster is challenging in islanded topology. This paper presents an intelligent controller for power sharing among PV-based MG clusters with load management of connected load during power deficiency. The priority is given to the local critical load of each MG. The second priority is given to the remaining load of the respective MG. The least priority is given to the loads connected to the neighboring MGs. The results show that the power continuation to the power-deficient load has been maintained when another MG has surplus power. The circulating current losses between the MG cluster has been fully avoided during no power sharing.

Efficient and seamless power management of hybrid generation system based-on DFIG wind sources and microturbine in DC microgrid

Abstract The study system in this paper is an islanded DC-microgrid comprising DFIG wind turbines (WTs), microturbine and loads. The main focus of this paper is on local control strategies design for the DFIG-WTs and microturbine to obtain short time-scale coordination, seamless power management and proper load sharing between WTs in the study system. In this work, control strategies related to the DFIG-WTs are extracted and then modified by adding an auxiliary control block, known as wind power curtailment block (WPCB), that adjusts the WT reference power according to the local DC bus voltages. Hence, as long as there is sufficient load demand, the WTs inject available power to the microgrid. Once available wind power exceeds the load demand, WTs adaptively curtail the injected power and seamlessly track the varying load. Next, the control structure of the so-called WPCB is further modified to realize proper load sharing between different WTs. Hence, by using the improved control structure of each WT, not only the proper and seamless power management is realized, but also, the load power is appropriately shared between different WTs according to available wind power. At the end, theoretical results are verified by time-domain simulations in the Matlab-Simulink environment.

A Distributed Iterative Learning Framework for DC Microgrids: Current Sharing and Voltage Regulation

With the penetration of computation intelligence, an increasing number of learning methods are developed into power engineering, such as dc microgrid applications. This paper establishes a distributed iterative learning framework to solve the current sharing and voltage regulation problem in an islanded dc microgrid from the perspective of game theory. The control objectives of dc microgrid include not only achieving the desired output current dispatch, but also regulating the voltage of dc bus to its rated value. Based on the two objectives, local performance indexes are established and an N -player game is formulated. Each source aims to minimize its own performance index and to achieve the current sharing objective simultaneously. Under the framework of game theory, a distributed iterative learning algorithm is designed based on the Bellman optimality principle and subsequently carried out using the approximate dynamic programming technique. The proposed algorithm is data based where it does not require to have the accurate model parameters of the dc microgrid and it ensures that the dc microgrid falls into a Nash equilibrium. Furthermore, a rigorous convergence analysis of the proposed algorithm is given. To demonstrate the effectiveness of the proposed method, simulation examples are presented on a tested dc microgrid.