Converters In DC Microgrids Research Articles

A New Wide Range and High Voltage Conversion Bidirectional DC/DC Converter for DC Microgrid

ABSTRACTBidirectional DC/DC converters (BDCs) are crucial in energy storage integration with DC microgrid. In this article, a new wide‐range and high voltage conversion (VC) nonisolated BDC with simple structure having reasonable components (total 13) is proposed. The proposed BDC with symmetrical VC ratio delivers high conversion of voltage within the vicinity of 0.5 duty ratio in both boost and buck modes of operation. In addition, the proposed BDC has features of continuous currents at low and high voltage stages and reduced switch voltage stress. This article presents the proposed BDC with circuit configuration and its detailed steady‐state boost and buck mode analyses to verify achievable VC ratio and design consideration. With the designed practical model of the proposed BDC, loss analysis is exhibited to verify the conversion efficiency in boost and buck modes of operation. In real time, experimental prototype of the proposed BDC is operated with LAUNCHXL‐F28379D kit to realize switching pulse generation. The experimental response of the entire proposed BDC operation is captured at 200 W loading. The attained experimental results and discussions validate the proposed BDC operation with the mentioned features. Finally, a comparative analysis with existing BDCs is performed to prove the competence of the proposed BDC for DC microgrid.

On the optimal game control in the DC microgrid systems

AbstractThis paper introduces static and dynamic competitive optimal control of DC/DC converters in DC microgrids based on game theory considering mutual effects. Using static and dynamic game theories, the conditions for competitive optimal control of DC/DC converters in Nash equilibrium with static and dynamic states are determined. Also, to reduce the complexity in the design of competitive optimal control of DC/DC converters due to the bilinear dynamic model of the system, generalized objective functions are considered. The competitive optimal controls using the Lyapunov and Riccati equations are determined to track the system trajectory to Nash equilibrium. Also, the numerical and experimental results are presented and compared in several cases. The results show that the competitive optimal control of the DC/DC converters in the DC microgrids can effectively improve the performance of the system.

An Improved Current Ripples Minimization Technique for Cascaded DC–DC Converter in DC Microgrid

An Improved Current Ripples Minimization Technique for Cascaded DC–DC Converter in DC Microgrid

An Adaptive Extended Kalman Filter With Passivity-Based Control for DC-DC Converter in DC Microgrids Supplying Constant Power Loads

This paper proposes an adaptive nonlinear control strategy to eliminate the instability problem of buck converters in DC microgrids (DCMG) considering constant power load (CPL). The strategy includes an Adaptive Passivity-Based Controller (PBC) and an Adaptive Extended Kalman Filter (AEKF). The proposed AEKF performs faster and more accurately than the conventional EKF and adjusts the covariance matrices adaptively. Furthermore, this AEKF directly estimates the unknown CPL power supplied by the converter and prevents the number of measurement sensors from increasing. Hence, PBC ensures system stability alongside AEKF. The controller guarantees Lyapunov stability and fast dynamic response in the presence of uncertainties and perturbations compared to other nonlinear methods. MATLAB simulations and laboratory implementation are provided to confirm the performance and robustness of the proposed control strategy and validate the analysis.

Current-Limiting-Type Fault Ride-Through Control Scheme for Converters in DC Microgrid

Current-Limiting-Type Fault Ride-Through Control Scheme for Converters in DC Microgrid

A comprehensive overview of DC‐DC converters control methods and topologies in DC microgrids

AbstractMicrogrids with large‐scale photovoltaic systems constitute a large part of distributed renewable generation in many grids around the world. Managing the performance of such microgrids and especially their interaction with the main power grid is a challenging task, because it requires the control of renewable resources. This paper presents a comprehensive overview of DC‐DC converter structures used in microgrids and presents a new classification for converters. This paper also provides an overview of the control techniques of DC‐DC converters in DC microgrids and the advantages and disadvantages of the control methods are discussed. In connection with the increasing penetration of distributed generation sources (DGS) and renewable sources in power systems and their power management has been raised as a major concern and methods for power management have been investigated in this paper. Finally, a DC microgrid system, which includes a solar system, wind turbine, and battery, is simulated in MATLAB/Simulink software and its performance is analyzed.

A coordination control strategy for parallel-connected boost converters in dc microgrid

Due to the constant power loads (CPLs), the system damping of the DC microgrid is reduced, which will lead to the collapse of bus voltage. In addition, the errors of current sharing amplify due to different line impedances. To address these issues, a hybrid coordination control strategy is proposed for parallel-connected boost converters, which realizes stable control and maintains the accuracy of the current distribution. Firstly, a passivity-based control (PBC) with a proportional-integral (PI) regulator is developed. The virtual damping-based PBC enhances the system damping and the PI regulator eliminates errors. On this basis, a secondary voltage control (SVC) featuring simplicity and weak dependence on communication is introduced to remove the errors of current distribution. Finally, the hybrid coordination control strategy is verified by RT-LAB-based hardware in the loop (HIL) experiment.

An adaptive voltage control compensator for converters in DC microgrids under fault conditions

This paper proposes a voltage compensator for converters in multi-converter DC microgrids (MG), which enhances the DC-MG behavior under fault conditions. Among the four existing categories in the classification of the faults, this paper focuses on those faults that affect voltage generation of converter-based distributed generation units (DGUs). Such faults conceptually occur from the terminal voltage reference to actual voltage generated by DGUs. To compensate the adverse effects of the faults, an adaptive scheme is proposed, which considers the most general case of the faults by using the time-varying multiplicative and additive fault models. The proposed scheme benefits from an integrated structure, which does not require separate fault detection, isolation, and identification blocks. As an advantage of the proposed approach, it is designed independent of the primary and secondary controllers of DGUs, and hence its performance is not affected by using different primary and secondary controllers. The effectiveness of the proposed scheme is verified under various fault conditions and uncertainty in the system parameters. Using the proposed scheme, the results show that the performance of system under the fault condition is similar to that of the normal operation.

Robust internal model-based voltage control for DC microgrids: An LMI based H∞ control

This paper aims to design a robust internal model-based voltage control (RIMVC) scheme for DC Microgrids (DCMGs) in the presence of unknown external disturbances. Maintaining voltage reference tracking under measurement noise, delays, model parameter uncertainties and unknown external disturbances while the load changes simultaneously is a severe challenge for the DC-DC converters in DCMGs. By developing a modified internal model-based voltage control for DC-DC converters, this work proposes a plug-and-play (PnP) robust voltage control scheme to address the abovementioned challenge. The proposed control method has a cascade structure. In the first step, a modified IMC control is designed to achieve desired tracking performance for a nominal dynamical system. In the next step, the output feedback H∞ control part is added to improve the performance robustness under external disturbances and parameter uncertainties. The efficiency of the proposed control scheme is evaluated using a real-time MATLAB/Simulink testbed, taking into account unknown internal and external disturbances under various rapid voltage reference changes, model parameter uncertainties, constant power loads, system delays and normal load profile changes in multiple case study scenarios.

Mismatched Disturbance Compensation Enhanced Robust H$_\infty$ Control for the DC-DC Boost Converter Feeding Constant Power Loads

A new control scheme to enhance the robustness and disturbance rejection ability of a DC-DC boost converter feeding constant power loads (CPLs) is proposed in this paper via introducing mismatched disturbance compensation into the robust H <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{_\infty}$</tex-math></inline-formula> control. In cascaded DC power converter systems, the load side converters, when tightly controlled, behave as CPLs for their source side converters, where the nonlinearities could result in severe instability. Besides, for power converters in DC microgrids, both the uncertainties/disturbances and the unpredictable load access could result in severe challenges to achieving higher control performance. In particular, the unknown CPLs must be considered as part of disturbances that form the so-called mismatched disturbances. To counteract these negative factors, a practical exact feedback linearization method is used to transform the control problem of a nonlinear system into that of a linear system, and the compensation of mismatched uncertainties/disturbances is introduced into the robust H <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">$\boldsymbol{_\infty}$</tex-math></inline-formula> control design. Moreover, sufficient conditions to ensure the asymptotic stability and robustness of system are established. Both simulation and experimental results confirm the efficiency.

Fuzzy logic feed-forward impedance shaping of DAB converter in DC microgrid with CPL load

Fuzzy logic feed-forward impedance shaping of DAB converter in DC microgrid with CPL load

Parallel control strategy of energy storage interface converter with virtual DC machine

To improve the inertia and damping properties of the energy storage units (ESUs) interface converters in DC microgrids, an enhanced virtual DC machine (VDCM) control technique based on traditional P-U droop control is proposed in this paper. The control scheme actively introduces additional inertia and damping to the converter by equivalently analogizing the P-U droop control of the energy storage converter with the speed control of the DC machine. With the proposed control scheme, the operation stability of the DC microgrid can be improved effectively. Due to the problem that the energy storage interface converter under VDCM control cannot achieve power distribution, a coordinated control method of power proportional distribution of parallel energy storage converter is proposed. A small signal model is established to analyze the influence of control parameter changes on system performance. The effectiveness of the proposed method is verified by the simulation, the results show that the proposed strategy can actively introduce greater inertia and damping for the converters to improve the inertia and damping characteristics of the energy storage converter. At the same time, it can play a dynamic adjustment effect when the energy storage interface converters are connected in parallel, which can make each converter distribute power according to the set proportion in the three working modes of charging, discharging and charging and discharging switching.

Model predictive control and linear control of DC–DC boost converter in low voltage DC microgrid: An experimental comparative study

It is challenging to select the best control strategy to regulate the output voltage of a DC–DC boost converter in DC MicroGrids (MGs). Indeed, the controller must cope with the standard requirements: robustness, steady-state and dynamic performance. Moreover, it also needs to handle the boost converter’s intrinsic Non-Minimum Phase behavior that significantly increases the difficulty from the control point of view. This paper compares four control methods (Linear Controller-based Voltage-Mode Control, Linear Controller-based Averaged Current-Mode Control, Finite Control Set Model Predictive Controller-based Voltage-Mode Control, and Finite Control Set Model Predictive Controller-based Current-Mode Control) based on experimental results. To achieve a fair comparison of the different control methods, an optimal design of the power converter parameters is proposed to minimize their influence on the controller’s performance. It provides some guidelines to select the appropriate controller. Several tests are performed on the experimental setup to evaluate the four control strategies, considering the features of DC MGs. Qualitative and quantitative comparisons are made regarding converter models, controller design, performance evaluation and implementation issues. The experimental results show that Finite Control Set Model Predictive Controller-based Current-Mode Control and Linear Controller-based Averaged Current-Mode Control are the best compromises.

Multivariable-Feedback Sliding-Mode Control of Bidirectional DC/DC Converter in DC Microgrid for Improved Stability with Dynamic Constant Power Load

In order to mitigate the influence of negative impedance characteristics on the stability of a DC microgrid with a constant power load, and the influence of nonlinear characteristics of a bidirectional converter on DC bus voltage, a control method of a bidirectional converter based on a multivariable-feedback sliding-mode control is proposed. The traditional control method usually uses the DC bus voltage error as a single controlled variable to optimize the design of the control law, which will lead to the lack of global coordination of each state variable. In this paper, the multi-state process variables-feedback sliding-mode control of a bidirectional DC/DC converter is designed, which can effectively improve the stability of the DC bus voltage, despite dynamic power disturbances. Firstly, the model of a bidirectional DC/DC converter, as well as the state equations of a converter with constant power load and resistive load, are analyzed. Secondly, to express various dynamic characteristics of the DC bus voltage fluctuation process, the output voltage error, the inductor current error and its integral are defined as the controlled state variables. Then, the multivariable weight combination-based sliding-mode surface is defined, and the sliding-mode controller is derived from a fast exponential power reaching law. Thirdly, the existence and stability of the multivariable-feedback sliding-mode control and the choice of control law parameters are discussed. Finally, MATLAB / Simulink software is used to simulate the proposed controller. Compared with PI and intelligent PID controllers, the proposed controller has the fastest response speed, the smallest steady-state voltage deviation and the best adjustment performance.

Learning-Based Model Predictive Control of DC-DC Buck Converters in DC Microgrids: A Multi-Agent Deep Reinforcement Learning Approach

This paper proposes a learning-based finite control set model predictive control (FCS-MPC) to improve the performance of DC-DC buck converters interfaced with constant power loads in a DC microgrid (DC-MG). An approach based on deep reinforcement learning (DRL) is presented to address one of the ongoing challenges in FCS-MPC of the converters, i.e., optimal design of the weighting coefficients appearing in the FCS-MPC objective function for each converter. A deep deterministic policy gradient method is employed to learn the optimal weighting coefficient design policy. A Markov decision method formulates the DRL problem. The DRL agent is trained for each converter in the MG, and the weighting coefficients are obtained based on reward computation with the interactions between the MG and agent. The proposed strategy is wholly distributed, wherein agents exchange data with other agents, implying a multi-agent DRL problem. The proposed control scheme offers several advantages, including preventing the dependency of the converter control system on the operating point conditions, plug-and-play capability, and robustness against the MG uncertainties and unknown load dynamics.

Decentralized Coordination and Stabilization of Hybrid Energy Storage Systems in DC Microgrids

Hybrid energy storage system (HESS) is an attractive solution to compensate power balance issues caused by intermittent renewable generations and pulsed power load in DC microgrids. The purpose of HESS is to ensure optimal usage of heterogeneous storage systems with different characteristics. In this context, power allocation for different energy storage units is a major concern. At the same time, the wide integration of power electronic converters in DC microgrids would possibly cause the constant power load instability issue. This paper proposes a composite model predictive control based decentralized dynamic power sharing strategy for HESS. First, a composite model predictive controller (MPC) is proposed for a system with a single ESS and constant power loads (CPLs). It consists of a baseline MPC for optimized transient performance and a sliding mode observer to estimate system disturbances. Then, a coordinated scheme is developed for HESS by using the proposed composite MPC with a virtual resistance droop controller for the battery system and with a virtual capacitance droop controller for the supercapacitor (SC) system. With the proposed scheme, the battery only supplies smooth power at steady state, while the SC compensates all the fast fluctuations. The proposed scheme achieves a decentralized dynamic power sharing and optimized transient performance under large variation of sources and loads. The proposed approach is verified by simulations and experiments.

Equal Current Sharing Parallelly Connected Interleaved Boost Converter in DC Microgrid using Control Algorithm

In this paper, a micro grid based current sharing between parallelly connected second order Boost Converter and Interleaved Boost Converter is proposed. As the output of PV is not predictable, an MPPT based on the Adaptive Neuro Fuzzy Inference System (ANFIS) is used to manage the second order Boost Converter. To offer exact sharing of current between parallel modules in converters, a droop control mechanism is utilized. The PV system’s maximum power is tracked using a PI controller, so as to maintain constant DC link voltage at different temperature conditions. Using a PI assisted Bidirectional battery converter, the voltage of the battery is maintained. The nominal voltage for each converter is modified by comparing each converter’s output current to the total load current. The entire system is validated through a MATLAB simulation.

A novel smooth switching control strategy for multiple photovoltaic converters in DC microgrids

A novel smooth switching control strategy for multiple photovoltaic converters in DC microgrids

Study on dynamic characteristic optimization of virtual inertia control for the grid-connected converters in DC micro grid

In order to reduce the transient time and voltage deviation due to voltage variation while increasing the system inertia of the DC microgrid, a new adaptive control method for the parameters of the grid-connected end is proposed. Firstly, a grid-connected converter control strategy mathematical model is established. Secondly, the influences of different control parameters on the dynamic characteristics of the system are studied. An adaptive equation based on the parameters of voltage deviation and voltage change rate of DC bus is proposed. Finally, through MATLAB/Simulink simulation, the simulation results of the traditional drooping control, the virtual inertial control with fixed parameters and the control strategy proposed in this paper are compared and analyzed. The result shows that the proposed control method has better dynamic characteristics.

Guest Editorial Special Issue on Topology, Modeling, Control, and Reliability of Bidirectional DC/DC Converters in DC Microgrids

DC microgrids have higher efficiency, better current carrying capacity, and faster response compared to the conventional ac systems. They also provide more natural interface with many types of renewable energy resources (RERs) and energy storage systems (ESSs), as well as better compliance with consumer electronics. These facts lead to increased applications of dc microgrid-type power architectures in remote households, data/telecom centers, renewable energy systems, electric vehicle charging stations, ships, aircrafts, and so on. Bidirectional dc/dc power converters (BDCs) constitute the fundamental building blocks of dc microgrids. They can be isolated or non-isolated and operated independently or in parallel to manage the power flow between sources and the dc microgrid. They can also be stacked together to operate in the so-called solid-state transformer architecture, which manages the power flow between dc microgrid and the upstream distribution network. The reliability, stability, efficiency, and power density of the BDC become very crucial for the dc microgrids. There are thus increasing research efforts made on the topology, modeling, control, and reliability of the BDC.