Operation Of DC Microgrid Research Articles

Consensus-based economic dispatch for DC microgrids incorporating realistic cyber delays

This paper introduces a distributed control approach for optimizing the operation of islanded DC microgrids (µGs), accounting for cyber delays and network failures. Initially, an integrated network emulation platform is utilized to calculate realistic cyber delays for islanded DC µGs employing IEC 61850 communication standard. To address the instability issues arising from cyber delays, the Artstein-Kwon-Pearson reduction technique is employed to convert the system with cyber delays into one without delays. The Subsequently, a consensus-based generation-cost optimization algorithm is designed for maintaining the economic operation of the µG. This algorithm efficiently equalizes the incremental costs (ICs) of all distributed generators (DGs) in a fully distributed manner, while adhering to the DGs capacity limits. Additionally, a fully distributed voltage regulation control is developed to stabilize µG average voltage, ensuring the balance between generation and demand. The efficacy of the formulated control technique is substantiated through diverse case studies, thereby underscoring its superior operational performance.

A Novel Machine Learning-Based Approach for Fault Detection and Location in Low-Voltage DC Microgrids

DC microgrids have gained significant attention in recent years due to their potential to enhance energy efficiency, integrate renewable energy sources, and improve the resilience of power distribution systems. However, the reliable operation of DC microgrids relies on the early detection and location of faults to ensure an uninterrupted power supply. This paper aims to develop fast and reliable fault detection and location mechanisms for DC microgrids, thereby enhancing operational efficiency, minimizing environmental impact, and contributing to resource conservation and sustainability goals. The fault detection method is based on compressed sensing (CS) and Regression Tree (RT) techniques. Besides, an accurate fault location method using the feature matrix and long short-term memory (LSTM) model combination has been provided. To implement the proposed fault detection and location method, a DC microgrid equipped with photovoltaic (PV) panels, the vehicle-to-grid (V2G) charging station, and a hybrid energy storage system (ESS) are used. The simulation results represent the proposed methods’ superiority over the recent studies. The fault occurrence in the studied DC microgrid is detected in 1 ms, and the proposed fault location method locates the fault with an accuracy of more than 93%. The presented techniques enhance DC microgrid reliability while conserving renewable resources, vital to promoting a greener and more sustainable power grid.

A dwell-time approach for decentralized grid-aware operation of islanded DC microgrids

In islanded microgrid (MG) applications, renewable-based distributed generation units (DGUs) are commonly operated in grid-feeding mode, while storage-based DGUs assume the grid-forming responsibilities. This results in limited controllable power reserves, which may pose severe threats to the overall system stability. Motivated by this, we consider the problem of designing a more flexible grid-aware control scheme for enlarging the actuation power of a DC MG. That is, existing DGUs are able to adopt different operation modes by switching among two decentralized passivity-based subsystem control laws in dependency of their node status. To this purpose, we design a time- and state-dependent switching logic that coordinates the DGU mode transitions and ensures that the closed-loop interconnected MG possesses a unique equilibrium point. Then, we derive sufficient tuning conditions on the control parameters that ensure global exponential stability of this equilibrium by adopting a multiple Lyapunov functions approach that exploits the passive interconnection properties of the MG together with dwell-time methods for switched systems. The advantageous performance of the proposed strategy is illustrated via a numerical example.

A Novel Nonisolated Four-Port Converter for Flexible DC Microgrid Operation

In this paper, a new non-isolated four-port DC-DC converter is proposed for DC Microgrid applications. The proposed converter offers a main feature of controlling the DC link voltage regardless of resources availability. By using four IGBT switches and only one diode, three different sources can be interfaced to a boosted DC link load. Different operation modes of the proposed architecture are discussed, testified and validated experimentally. The buck-boost capability of the proposed topology allows an enhanced flexibility to integrate various sources with distinct voltage-current (V-I) characteristics while sharing load power among all ports. In this context, steady state analysis is performed to determine the voltage gains between all ports. The control strategy is developed for the proposed topology to manage power flow between sources and load achieving basic operations for renewable resources such MPPT for PV. A theoretical based study is performed on the proposed converter including steady-state analysis, state-space averaging followed by small signal modeling and frequency response-based controller design. The converter different operating conditions are validated experimentally.

Operation Analysis of Coordinated Droop Control for Stand-alone DC Micro-grid

This paper introduces a coordinated droop control for the stand-alone DC micro-grid., which is composed of photo voltaic generator, wind power generator, engine generator, and battery storage with SOC (state of charge) management system. The operation of stand-alone DC micro-grid with the coordinated droop control was analyzed with computer simulation. Based on simulation results, a hardware simulator was built and tested to analyze the performance of proposed system. The developed simulation model and hardware simulator can be utilized to design the actual stand-alone DC micro-grid and to analyze its performance. The coordinated droop control can improve the reliability and efficiency of the stand-alone DC micro-grid

A new control method of hybrid energy storage system for DC microgrid application

AbstractEnergy storage system play a crucial role in safeguarding the reliability and steady voltage supply within microgrids. While batteries are the prevalent choice for energy storage in such applications, their limitation in handling high‐frequency discharging and charging necessitates the incorporation of high‐energy density and high‐power density storage devices to enhance power quality, maintain power balance, and reduce fluctuations. In this study, we introduce a hybrid energy storage system (HESS) solution, combining a battery and a supercapacitor, to address intermittent power supply challenges. The effective management of this HESS is pivotal for constant DC voltage and sustaining microgrid stability. To achieve this, we propose an innovative control strategy called the Adaptive Filter‐Based Method (AFBM) for DC microgrid operation, which prioritizes stable and smooth performance while addressing safety and degradation concerns related to the storage devices. Our control strategy determines the distribution of charging and discharging currents for each storage device within the DC microgrid based on their state of charge. We conducted simulations in MATLAB/Simulink, comparing the proposed AFBM method with the conventional filter‐based approach using identical configurations, parameters, and operational modes. The results demonstrate the superior performance of our proposed system, showcasing improved voltage stability, more equitable load distribution, and efficient charging and discharging of storage devices compared to the traditional method. This research contributes to the advancement of microgrid energy storage solutions, enhancing their reliability and performance.

Smooth and Uninterrupted Operation of Standalone DC Microgrid Under High and Low Penetration of RESs

Smooth and Uninterrupted Operation of Standalone DC Microgrid Under High and Low Penetration of RESs

DC-Bus Signaling control laws for the operation of DC-microgrids with renewable power sources

DC-Bus Signaling control laws for the operation of DC-microgrids with renewable power sources

A Quadratic Formulation of ESS Degradation and Optimal DC Microgrid Operation Strategy Using Quadratic Programming

A Quadratic Formulation of ESS Degradation and Optimal DC Microgrid Operation Strategy Using Quadratic Programming

Differential Reactor Voltage Based Fault Detection and Classification for Smart DC Microgrid

The primary challenges in the implementation of differential protection techniques are Time Synchronization Error (TSE) due to communication delay and low sensitivity towards High Resistance Faults (HRFs). In this paper, a new technique utilizing the difference in voltage measured across the external reactors connected at opposite ends of the cable is proposed for fault detection and classification of HRFs in islanded and grid connected mode of operation of DC microgrid. Further, to overcome the challenges associated with TSE, which causes differential schemes to mal-operate, the proposed technique determines reactor voltage polarity at opposite ends of the cable to distinguish between internal and external faults. The proposed technique is tested for different types of internal faults and system transients such as external faults, load switching, generation uncertainties etc. to demonstrate sensitivity and accuracy of the proposed technique. Finally, a comparative analysis of the proposed technique is performed with the schemes reported in the literature, which confirms the fast fault detection, high sensitivity for internal HRFs, selectivity and stability of the proposed technique for different operating conditions.

Study on Energy Efficiency Improvement Strategies of Photovoltaic-Hybrid Energy Storage DC Microgrids under the Concept of Green Energy Conservation

Abstract To improve the energy efficiency of a PV-hybrid energy storage DC microgrid, a series of management strategies are proposed in this paper. According to the working principle of photovoltaic cells, the variable step conductance increment method is used to track and control the output power of photovoltaic cells, and the time constant of the low-pass filter is dynamically adjusted according to the output characteristics of supercapacitors in different SOC intervals, so as to put forward a limit management strategy based on the supercapacitor’s SOC partitioning. An energy management strategy for PV DC microgrid based on hybrid energy storage is proposed to address the impact of internal power fluctuation on DC microgrid operation stability. Based on the voltage deviation range, the system is divided into five operation modes to achieve efficient distribution of system power. Through simulation verification, the charging state difference of the battery bank is reduced by 0.00537 after a charging process of 20 s under the withdrawal and addition of PV power, and the charging power ratio is 5.00:8.14:6.82 at steady state under the withdrawal and addition of the hybrid energy storage unit, U dc = 405.4V. This paper’s strategy makes the DC microgrid effective in improving energy efficiency and smoothing out power fluctuations in all operating modes.

Voltage Stability Assessment of a Campus DC Microgrid Implemented in Korea as a Blockchain-Based Power Transaction Testbed

Recently, the generalization of P2P (peer-to-peer) technology with enhanced security due to blockchain technology and the expansion of renewable energy-based distributed energy resources have led to blockchain technology being applied in power transactions, thus giving the potential to become a new platform for DC microgrid operation. Meanwhile, the voltage of a DC microgrid represents the balance of energy supply and demand and also serves as a stability index. The balance is represented as a steady state; the stability is represented during and after events. This paper examines the stability of the DC microgrid built on a university campus in Korea and, in particular, the blockchain technology-based power transactions performed in the DC microgrid. The test is based on the pre-planned transaction schedule applied in the DC microgrid. The transaction schedule has used day-ahead and real-time bidding data. Although many technologies are included in the project, this paper focuses on the voltage stability of the DC microgrid. In addition, the DC protection is applied and evaluated. To consider general DC protection, the DC breaker was simplified with several IGBTs, diodes, capacitors, and arrestors and was designed to interrupt the fault current within five milliseconds. The stability was evaluated using a PSCAD/EMTDCTM.

SELECTION OF THE NON-ISOLATED UNIDIRECTIONAL DC-DC CONVERTERS FOR PHOTOVOLTAIC APPLICATIONS

The rising prominence of renewable energy sources and the demand for efficient power distribution has led to the emergence of DC microgrids as a promising solution for localized energy generation and distribution. The effective operation of DC microgrids heavily relies on the performance of their DC-DC converters, which play a crucial role in regulating power flow and voltage. Selecting suitable DC-DC converters is thus essential to ensure optimal performance and stability of photovoltaic systems. This academic article presents a comprehensive comparative analysis of different non-isolated DC-DC converter topologies and their appropriateness for DC microgrid applications. The research delves into various converter types, including buck, boost, buck-boost, SEPIC, and Zeta converters, thoroughly examining their operating principles, control strategies, and advantages within the context of DC microgrids. The focus is on key performance metrics essential for a comprehensive evaluation, including efficiency, voltage regulation, transient response, power density, and cost-effectiveness. Through meticulous comparative analysis, it is established that the SEPIC and Zeta converters stand out as exceptional choices for DC microgrids. Their distinct advantages, such as reduced output ripple, improved efficiency, and wide input voltage range, position them as valuable contenders for modern power electronics applications, showcasing their excellence in addressing diverse voltage regulation needs. This academic article contributes valuable insights into the selection and application of DC-DC converters in DC microgrid systems, providing researchers, engineers, and industry stakeholders with a comprehensive understanding of the comparative advantages of these converters. The findings underscore the significance of choosing appropriate converters to achieve efficient energy conversion, optimal power distribution, and the advancement of renewable energy technologies in the context of DC microgrids. Keywords: DC-DC converters, SEPIC, ZETA, BUCK, BOOST.

Centralized Energy Management Scheme for Grid Connected DC Microgrid

Energy management in DC microgrid is complex and challenging due to the stochastic nature of renewable energy sources and load demand. Coping with the deficit power, peak demand, and power converter control operations are a few major concerns. The photovoltaic (PV) system and battery energy storage system (BESS) utilization need special attention for the reliable and efficient operation of the DC microgrid. Hence, this article proposes the centralized energy management scheme (CEMS) in the DC microgrid to address the abovementioned challenges. The CEMS coordinates among the various physical layer components and computational layer (i.e., control layer) of the DC microgrid. It utilizes the multioptimization for energy management during the peak and <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> -peak load demand, optimal usage of PV-BESS, and performs the optimal load shedding operation. Furthermore, an optimal utilization of the PV-BESS problem is formulated and solved using linear programming to avoid excess usage of AC grid power. In deficit PV power, the optimal load shedding operation is formulated as mixed-integer linear programming problem to ensure the DC bus voltage regulation and power balance. The proposed CEMS demonstrates the effective operation of the PV system in maximum power point tracking, <sc xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">off</small> -MPPT mode (i.e., voltage control), and BESS's charging/discharging operation. It is showcased that the hierarchical control structure of CEMS improves the performance, efficiency, and reliability of the DC microgrid operation. Hence, a 48 V and 1.2 kW PV-BESS-based DC microgrid system is developed to show the efficacy of the proposed algorithm under different scenarios in MATLAB/Simulink. The real-time simulator results of the developed system, obtained using OPAL-RT OP4510, confirmed the effectiveness and reliability of the proposed scheme.

Adaptive filter based method for hybrid energy storage system management in DC microgrid

Based on previous energy storage technology research, no single energy storage device combines the high energy density and high power density. Hybrid energy storage system combines multiple energy storage technologies to achieve enhanced performance and efficiency in energy storage applications. This paper proposes a hybrid energy storage system that consists of batteries and supercapacitors for maintaining the stable functioning of DC microgrids. However, effective control and management systems are necessary to maximize their performance. This paper proposes a novel adaptive Frequency-Based Control with State of Charge management as a solution for achieving smooth operation of DC microgrids. By utilizing the state of charge of high power density and high energy density energy storage systems as control inputs, the proposed method adjusts the current flow into the storage devices, resulting in improved power management, accurate voltage regulation, enhanced SOC control, and increased system stability. The proposed adaptive control method is compared to the conventional Frequency-Based Control through MATLAB/Simulink simulations using the same configuration, operation mode and parameter value. In the case studies, the proposed method demonstrates a reduction of 6.7% in peak voltage and 30% in dip voltage compared to the conventional method. Moreover, the settling time of the proposed method is improved by 0.9 and 0.03 s, respectively, compared to the conventional method. The results demonstrate that the proposed method outperforms the conventional method, providing better power management, faster and more precise voltage regulation, and enhanced SOC control.

Stability Constrained Optimal Operation of Standalone DC Microgrids Considering Load and Solar PV Uncertainties

Operation and control dynamics of islanded DC microgrids (DC mGs) have received enormous interest recently in distribution system management. In this regard, research concern on droop-controlled distributed generations (DGs) integrated within the standalone DC mG is becoming more profound. This paper proposes an optimal operation of droop-controlled standalone DC mG with combined small-signal stability and economic-environment-related objectives. The proposed approach optimizes the principal eigenvalue that affects the system stability and two other objectives. An eigen value-based stability analysis for network configurations, with the possibility of its buses solely connected to either dispatchable DG or constant power load (CPL), is proposed. Moreover, uncertainties involved in mG network variables that originate due to the integration of solar PV generation with load consumption were considered and modelled with relevant probability characterization. A recent swarm-based intelligent technique (dragonfly algorithm) for optimization of droop parameters is adopted in the proposed approach. A unique bi/tri-objective combinations are solved, and obtained results are discussed. To show the adaptability of the proposed approach for any given DC mG network, a standalone 6-bus mG was adopted to verify the applicability. Furthermore, the time-domain simulations were carried out on a sample 3-bus DC mG to validate the proposed strategy.

Power pool‐based supervisory coordinate control strategy for DC microgrids

SummaryStandalone DC microgrids are progressively becoming explored in the modern power system. Proper voltage regulation and effective power distribution among sources are the main challenges for DC microgrid operation. A supervisory coordinated control strategy for proportionate power‐sharing and enhanced voltage regulation is presented in this paper to overcome these challenges. The formation of multiple power pools on the basis of available power from each renewable energy source (RES) is a crucial element of this approach. It modifies the power sharing between power pools and individual sources based on the amount of power available in the sources. In addition, for effective power management, it coordinates the operation of all power pools with all RESs. Also, by reducing the charging and discharging cycle of energy storage systems (ESSs), it is possible to make effective use of ESSs. The proposed control adapts to intermittent RESs and changes in the microgrid network. The proposed method's capabilities are validated by experimental results.

Intelligent Island detection method of DC microgrid based on Adaboost algorithm

Aiming at the problems of large detection blind areas and difficult threshold settings in traditional passive islanding detection methods, this paper proposes an intelligent passive islanding detection method based on the adaptive boosting (Adaboost) algorithm. This method first uses feature screening technology to obtain the key feature electrical quantities of DC microgrid islands and form a sample set, and then rely on the Adaboost algorithm to generate a high-precision island classification model to realize the detection and classification of DC microgrid operation status. It has the advantages of automatic setting threshold, small detection blind area, and high accuracy. In addition, aiming at the problem that the classification results of the intelligent islanding detection algorithm based on machine learning cannot be directly used as the islanding discrimination results, an islanding criterion method based on the sliding window algorithm is added on the basis of the classification algorithm. This method realizes the accurate detection of the DC microgrid islanding operation state by the secondary analysis and judgment of the classification results of the islanding classification model. Finally, a DC microgrid model is built to simulate and verify the proposed method. The results show that the method can quickly and accurately complete the islanding detection of the DC microgrid.

Accurate power sharing for islanded DC microgrids considering mismatched feeder resistances

Accurate load power sharing and bus voltage regulation are two critical control objectives for ensuring power quality and reliable operation of DC microgrids. Although regulating the DC Bus voltage can be achieved by adopting an external secondary control loop, inaccurate load power/current sharing among converters is a prominent issue due to feeder resistances mismatch. This can lead to undesired overloading of converters, triggering over-current protection relays, and potentially resulting in cascading failure of the whole system. Existing literature uses virtual resistance techniques to improve the power sharing accuracy; however, so far, no explicit relation between the values of the virtual resistances and the feeder resistances mismatch has been formulated, opening the possibility to enhance power sharing even further. Therefore, this paper proposes an accurate power sharing strategy in which the virtual resistances are chosen to account for the feeder resistances mismatch. The proposed technique relies on the optimal tuning of the virtual resistance assigned to the local controller of each converter. An online estimation algorithm of the physical feeder resistances, required for virtual resistance tuning, is embedded into the control loop of each converter. Thus, prior information about the feeder resistances in the design stage is not required. The proposed approach is validated through simulation and experimental results from a Hardware-in-the-Loop setup of a typical islanded DC microgrid. The results demonstrate the approach merits, achieving accurate power sharing among converters and ensuring robust operation, even in scenarios involving communication failures.

Optimal Scheduling of DC Microgrids based on MOPSO Algorithm

The DC microgrid system contains a variety of distributed power sources, but the distributed power sources are uncertain and intermittent. In order to improve the economy of DC microgrid operation, mainly to reduce the microgrid operation cost and environmental management cost, and at the same time the largest proportion of scenery consumption, the optimization algorithm is effective for microgrid for optimal scheduling. A multi-objective optimal scheduling model for microgrids is established. A microgrid model with wind, photovoltaic, micro gas turbine and energy storage is constructed and solved using a multi-objective particle swarm algorithm. The multi-objective particle swarm algorithm is invoked for a typical 24h daily isolated micro-grid system in a certain region. The simulation results show that the optimal dispatching scheme can effectively improve the economy of the microgrid, reduce its operating costs as well as the ability to consume renewable energy scenery power.