Control Of DC Microgrids Research Articles

Forecast-Based Consensus Control for DC Microgrids Using Distributed Long Short-Term Memory Deep Learning Models

In a microgrid, renewable energy sources (RES) exhibit stochastic behavior, which affects the microgrid continuous operation. Normally, energy storage systems (ESSs) are installed on the main branches of the microgrids to compensate for the load-supply mismatch. However, their state of charge (SoC) level needs to be balanced to guarantee the continuous operation of the microgrid in case of RES unavailability. This paper proposes a distributed forecast-based consensus control strategy for DC microgrids that balances the SoC levels of ESSs. By using the load-supply forecast of each branch, the microgrid operational continuity is increased while the voltage is stabilized. These objectives are achieved by prioritized (dis)charging of ESSs based on the RES availability and load forecast. Each branch controller integrates a load forecasting unit based on long short-term memory (LSTM) deep neural network that adaptively adjusts the (dis)charging rate of the ESSs to increase the microgrid endurability in the event of temporary generation insufficiencies. Furthermore, due to the large training data requirements of the LSTM models, distributed extended Kalman filter algorithm is used to improve the learning convergence time. The performance of the proposed strategy is evaluated on an experimental 380V DC microgrid hardware-in-the-loop test-bench and the results confirm the achievement of the controller objectives.

Dynamic compensation control strategy of DC bus voltage based on residual generator.

Aiming at the problem of bus voltage control in DC microgrid, a dynamic compensation control strategy based on a residual generator is designed to complete the voltage compensation of DC-DC converter. Firstly, based on the DC microgrid system architecture, the bus voltage fluctuations are analyzed theoretically, and then the DC-DC converter state-space mathematical models of the DC microgrid system are established to obtain the input-output relationship of the control system. Based on the theory of double coprime decomposition and Youla parameterization stable controller, the proposed control architecture based on the residual generator is obtained, and the output value generated by the current disturbance is compensated in reverse by applying model matching theory. The voltage loop compensation controller Q(s) is obtained by the linear matrix inequality method (LMI), and the current loop compensation controller H(s) is designed according to the dynamic structure diagram of the DC-DC converter. Hardware-in-the-loop simulation (HILS) results show that the architecture can improve the dynamic performance of the DC-DC converter without changing the original system structure parameters, and suppress the DC bus voltage fluctuations caused by load switching, power fluctuations, and AC-side load imbalances, and enhance the robustness of the system.

Coordinated Control for Islanded DC Microgrid Considering Power Sharing of Multiple Energy Storages

Coordinated Control for Islanded DC Microgrid Considering Power Sharing of Multiple Energy Storages

Data-Driven Passivity-Based Control Design for Modular DC Microgrids

This article contains a new passivity-based control design approach for dc microgrids. The design is purely based on experimental data—bypassing the requirement of the network modeling. This approach permits the control of dc microgrids and preserve stability, despite of further interconnection of new passive loads and new passivity-based-controlled converters. This model-free approach generates control laws in a pure numerical way; bypassing the requirement of dealing with a high number of variables and equations that naturally appear in an increasingly complex dc microgrid. Experimental results are presented to corroborate the advantages of our approach.

Comparative analysis on the stability mechanism of droop control and VID control in DC microgrid

Voltage resonance and fluctuation deteriorate the stability of DC microgrids (DC-MGs) and restrict their popularization. Conventional droop control cannot suppress voltage fluctuation and damp oscillations. Therefore, new control methods, namely, droop+filter control and virtual inertia and damping control, are proposed. These methods differ owing to the addition of low pass filter (LPF) and virtual inertia loop. In this study, the stability of these control methods is investigated comprehensively to understand their differences arising from the use of LPF and inertia loop as well as the underlying dynamic stability mechanism. The leading causes of voltage instability in DC-MGs regulated by droop control are first presented. Subsequently, control methods for solving this issue are compared and their simplified small-signal models are constructed. Based on eigenvalue analysis, the DC-MG is equivalent to a third-order system. Different control effects can be acquired by changing the control parameters and the location of the eigenvalues; furthermore, they can be used to understand the dynamic stability. Eigenvalue analysis can provide parameter design guidelines. Finally, the simulation results verify the validity of the theoretical analysis.

Decentralized Model Predictive Control of DC Microgrids With Constant Power Load

This article introduces a decentralized model predictive controller (DMPC) to ensure power sharing and regulate dc bus voltage in dc microgrids (MGs) with a constant power load (CPL). The proposed method replaces the conventional primary layer of dc MGs, i.e., inner loops and droop control, with a single optimal controller. A predictive automatic model of the system is realized for prediction purposes and to be used in the cost function. The control objectives are then incorporated in the cost function to attain an optimal state switching in each sampling time, hence regulating the dc bus voltage and accurate sharing of current among the MG. The proposed solution provides the system with a fast dynamic response and a zero steady-state error. The effectiveness of the proposed control is verified by hardware-in-the-loop (HIL) real-time experiments, and the results are compared with the conventional primary control.

Improved droop control of DC microgrid based on virtual impedance

In order to solve the problem of distributed energy generation, microgrid has been proposed as one of the options. Compared with AC microgrid, DC microgrid is more suitable for many current distributed power equipments. In order to ensure the stable operation of the DC microgrid, it is necessary to develop an effective energy management strategy. As a typical method of current distribution, droop control has been widely studied and discussed. Traditional droop control has inherent limitations, so this paper proposes an improved method for droop control.

Fuzzy logic control (FLC)-based coordination control of DC microgrid with energy storage system and hybrid distributed generation

ABSTRACT The developed and developing countries are going to install a number of distributed generations (DGs) with lucrative incentives. In recent years, DC microgrids have got remarkable popularity throughout the world due to dc output sources, namely, batteries, solar panels, and fuel cells are interconnected without the presence of ac/dc conversion. In this paper, the photovoltaic (PV) system is proposed with the fuel cell (FC) and battery bank in the micro-gird system at various dynamic conditions. Besides, fuzzy logic controller is suggested to regulate the bus voltage and retain the power balance. In order to ascertain the effectiveness of the suggested control approaches, the system has been verified with various dynamic conditions like 50% changes in AC and DC loads, irradiance variations, overloading situations and the battery bank functioning when the change in FC is observed. The simulation outcomes disclose that the fuzzy-based proposed method renders better dynamic performances with proposed energy storage systems.

Decentralized Voltage Control of Autonomous DC Microgrids With Robust Performance Approach

In this article, we propose an optimal decentralized robust <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$H_\infty $ </tex-math></inline-formula> control system for the voltage control problem of autonomous uncertain dc microgrids consisting of multiple distributed generations (DGs) with general topology. The one-degree-of-freedom (DoF) structure of the developed control system guarantees the robust performance of the system as well as its robust stability against various sources of uncertainty, such as plug-and-play (PnP) operation of the DGs, topology changes, large load perturbations, different subsequent system changes, and the presence of constant power loads (CPLs). To that end, the uncertain dc microgrid is modeled as a Linear Time-Invariant (LTI) polytopic state-space system. Then, a state-feedback control technique based on linear matrix inequality (LMI) with linearly parameter-dependent (LPD) Lyapunov matrices is implemented on the uncertain dc microgrids. The proposed controller does not require any sort of communications, and the robust performance property of the controller eliminates the need for prefilter design. The efficiency of the proposed controller is analyzed by simulating different case studies through SimPowerSystems Toolbox in MATLAB. Finally, the performance of the proposed control method is validated via experimental studies.

DC microgrid small-signal stability and control: Sufficient stability criterion and stabilizer design

The behavior of constant power loads is known to be a potential cause of instability in DC microgrids. This issue is addressed by the DC microgrid stabilizer proposed in this paper. It relies on active stabilization through power electronic control by introducing a virtual positive resistance to counteract the negative incremental resistance of a constant power load. Compared with physical damping resistors, the virtual counterpart does not incur heat losses. It also has no adverse impact on microgrid power sharing nor on voltage regulation. The theoretical foundations for the design of the stabilizer were made possible thanks to the method of DC microgrid modeling and analysis also developed here. To obtain a model of general validity and practical value, the behavioral characteristics of all components connected to DC microgrid buses are mapped onto two elementary categories. With the DC microgrid model then obtained in nonlinear state-space format and subsequent linearization, a sufficient criterion of stability is readily obtained. It gives the rule for tuning the DC microgrid stabilizer. The simulation tests confirmed the validity of the modeling and analysis framework as well as the performance of the stabilizer.

Deception Attack Detection of Isolated DC Microgrids Under Consensus- Based Distributed Voltage Control Architecture

A consensus-based distributed voltage control architecture of isolated DC microgrids (MGs) with deception attack awareness is investigated in this paper. Firstly, a fully distributed voltage control algorithm with only adjacent information sharing is proposed by expanding the consensus-based distributed algorithm in AC MGs. To further enhance the ability of deception attack detection in the associated cyber network, an analytical consistency-based anomaly detection mechanism is also developed by manipulating primal variables and dual variables associated with the proposed distributed voltage control algorithm. Strategies for detecting either individual or stealthy false-data injection attacks on both links and nodes of the associated communication network against the distributed consensus-based droop control of DC MGs are investigated. Numerical experiments of a DC MG on real-time simulators are performed to validate the efficacy of the proposed deception attack detection mechanism.

Design of Nonlinear Droop Control in DC Microgrid for Desired Voltage Regulation and Current Sharing Accuracy

It is well known that there is a design tradeoff between voltage regulation and load current sharing in conventional linear droop control for several parallel-connected distributed sources in a DC microgrid. To improve both performance areas, this article proposes a design method to identify the nonlinear droop curve coefficient with the desired bus voltage regulation and current sharing accuracy in a specified heavy load range, while a linear droop function with a negative droop resistance is used to tighten the bus voltage regulation in the light load range. The design procedure of load boundary and the effect of negative droop resistances on the system stability are analyzed in detail. Also, a boost-up and curve-fitting method can further improve the voltage regulation and achieve smooth transition between light load and heavy load. In this way, no additional voltage compensation loop is needed. Two parallel-connected DC converters are finally built to verify the theoretical analysis.

An adaptive droop technique for load sharing in islanded DC micro grid with faulty communication

ABSTRACT The control of DC microgrids is a growing area of research. DC distribution networks present an effective solution to the integration of stochastic energy sources as renewable energy and renewable storages. A communication layer is required to exchange measured and estimated values for the secondary control loop. Faults and failures within the communication layer lead to malfunctions and divergence in system values. The control structure is presented using adaptive droop based secondary control for detection of communication islanding and stabilize the operation of the system. Recent years, more robust techniques and methodologies have been suggested to increase system resilience, but the communication islanding detection has not been addressed in DC microgrid at the multi-level control. This work, therefore, modifies the secondary level control to include a communication failure detection scheme that identifies communication islands within this network. Adaptive droop is employed to mitigate the effect of communication islands and regulate current sharing. The proposed scheme is verified using system-level simulations and analytical studies.

Analysis of Performance and Control of DC Microgrids as Electricity Providers for Renewable Energy

The increase in demand for electrical energy is increasing rapidly, in line with economic growth. In developing the electricity system, electrical energy service providers must provide electrical energy according to demand with good quality. The generation of conventional electric energy systems that use fossil fuels faces depleting fossil fuel sources, poor efficiency, and environmental pollution. This technology is known as Distributed Generation (DG). Distributed Generation (DG) or Micro Grid (MG) is a small-scale power plant located close to the load. The use of distributed generators can improve the entire system's efficiency, reduce transmission losses, reduce pollution, and ensure the continuity of the distribution of electrical energy. However, the drastic increase in the use of DG causes problems in the form of voltage and frequency stability which will be disturbed due to rapid changes in the generation and loading rates. If this is left unchecked, it can harm system security and reliability. A proper control strategy will restore system stability in the event of an imbalance.

Research on Active Protection and Control of DC Microgrid Based on Controlled IGBT

Research on Active Protection and Control of DC Microgrid Based on Controlled IGBT

Research on Strategy of DC Micro-grid Control and Protection

Introduction The control and protection technology of DC microgrid plays an important role in ensuring the reliable and safe operation of DC microgrid. The paper aims to solve the key technologies in the design of DC micro-grid. Method DC bus topology selection， control strategy， and protection configuration scheme were discussed in the paper. Result The selection principle of DC bus topology structure， the control strategy process of DC micro-grid， protection zone and configuration are given in the paper. At the same time， the selection of DC transformer is analyzed and compared. Conclusion The method has been validated in national demonstration projects， and it has performed well since it was put into operation.

Distributed Sliding Mode Observer-Based Secondary Control for DC Microgrids Under Cyber-Attacks

The conventional distributed secondary control is widely adopted for distributed energy resources (DERs) in DC microgrids to achieve bus voltage restorations and output current/power sharing. However, when the DER systems are under cyber-attacks, the control variables of the conventional distributed secondary control will deviate from the nominal parameters and the stability of entire DC microgrids may not be guaranteed anymore. To this end, a distributed sliding mode observer (DSMO)-based secondary control is proposed in this paper. Based on local and neighboring measurements, the DSMO initially detects the false signals. Then, the estimated false signals are compensated by the control variables of the secondary control to eliminate the adverse impact. The stability of DSMO is verified by the convergence of the state variables. Both simulation and experimental results have validated that the proposed DSMO-based secondary control can effectively regulate the DER systems to track the bus voltage references and the desired output current/power under various types of cyber-attacks.

Sensorless Control of DC Microgrid Based on Artificial Intelligence

Nowadays, DC microgrids are preferred in the field of renewable energy. The autonomous DC microgrids aim to provide smooth power flow from renewables to loads. While satisfying certain load profiles and sustaining the power as the desired level, the control of power converters is considerable. To ascend the resilience of DC microgrids, battery storage systems (BSSs) are also used as a backup unit for supplying uninterrupted power. The main task of BSSs is to compensate for the lack of power when the load is higher than supplied power or store the surplus of power in case that the load demand is less than the extracted power. In other words, by draining and storing the power, BSSs help to increase the flexibility of the system and keep the main DC bus voltage within acceptable bounds. This study introduces artificial intelligence (AI)-based method to diminish the number of implemented sensors and control power converters without reducing efficiency. In this paper, artificial neural networks (ANNs) as a subset of AI are exploited. Diminishing the number of sensors in the control layer makes the system more reliable. To validate the effectiveness of the proposed system, phases of ANNs' simulations are performed in MATLAB/Simulink.

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 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.