Standalone DC Microgrid Research Articles

Rule‐based energy management system for autonomous voltage stabilization in standalone DC microgrid

AbstractThis paper presents a rule‐based energy management system (EMS) designed for a standalone DC microgrid incorporating solar photovoltaic (PV), fuel cell, battery energy storage system (BESS), and electric vehicle. The unpredictable nature of renewable energy sources and the instability of loads pose challenges for maintaining DC bus voltages and power‐sharing arrangements, impacting the microgrid's smooth operation. The proposed EMS aims to ensure power balance between generation and demand, mitigating vulnerabilities of the DC bus to voltage instability caused by fluctuations from both the load and source sides. This is achieved through an autonomous DC bus voltage stabilization strategy, involving the maintenance of a nominal state of energy (SoE) for the BESS and hydrogen fuel consumption for the fuel cell within predefined lower and upper limits. By regulating these two factors, the EMS algorithm facilitates optimal performance of the PV, battery, and fuel cell components. Consequently, the EMS provides decision‐making instructions to each individual energy source, ensuring efficient operation under various conditions. The effectiveness of the proposed EMS is evaluated through hardware‐based testing on a DC microgrid and simulations in the MATLAB Simulink environment across multiple operating scenarios.

Hardware Implementation of Hybrid Data Driven-PI Control Scheme for Resilient Operation of Standalone DC Microgrid

Hardware Implementation of Hybrid Data Driven-PI Control Scheme for Resilient Operation of Standalone DC Microgrid

Multi‐objective optimisation framework for standalone DC‐microgrids with direct load control in demand‐side management

AbstractRenewable energy‐powered DC microgrids have emerged as a sustainable alternative for standalone power systems in remote locations, which were traditionally reliant on diesel generators (DIG) only. To ensure power quality and reliability, energy storage systems (ESS) and demand‐side management (DSM) techniques are employed, addressing the intermittent nature of renewable energy sources (RES). This manuscript presents a novel multi‐objective optimisation framework to determine the equipment sizing, depth of discharge (DoD) of ESS, and share of controllable loads contributing to DSM in a standalone DC microgrid incorporated with RES as a primary energy source and a backup DIG. The proposed optimisation strategy utilises genetic algorithm with the objectives of minimizing lifecycle cost and carbon footprint. A novel battery energy storage system (BESS) management criterion is introduced, which accounts for battery degradation in the lifecycle cost calculation. The minimum allowable DoD of the BESS is considered a decision variable in the optimisation problem to assess the impact of higher DoD on lifecycle cost improvement. MATLAB simulation results demonstrate that the proposed optimisation model significantly reduces the levelized cost of electricity and per unit carbon footprint compared to previous models. Additionally, it identifies an optimal range of DoD for the BESS to enhance the lifecycle cost of a standalone DC microgrid.

Distributed secondary control for proportional power sharing and DC bus voltage restoration in standalone DC microgrid

Distributed secondary control for proportional power sharing and DC bus voltage restoration in standalone DC microgrid

Improved Adaptive Network-Based Fuzzy Inference System Approach for Power Flow Analysis in Interconnected DC Microgrid

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

An effective data-driven machine learning hybrid approach for fault detection and classification in a standalone low-voltage DC microgrid

An effective data-driven machine learning hybrid approach for fault detection and classification in a standalone low-voltage DC microgrid

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

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

Robust next-day scheduling of PV generation sources supplying a standalone DC microgrid via a semi-definite programming model

Robust next-day scheduling of PV generation sources supplying a standalone DC microgrid via a semi-definite programming model

SOC Balance Control Strategy for Distributed Energy Storage System in DC Microgrid

By integrating a distributed energy storage system (ESS), a standalone DC microgrid can maintain power balance and voltage stability between distributed energy sources and loads. However, without establishing the relationship between the output power of the distributed energy storage units and their state of charge (SOC), inconsistent SOC among the storage units can occur. This inconsistency can lead to issues such as overcharging and over-discharging, significantly impacting the ESS lifespan. To address this, the paper proposes a SOC droop control scheme utilizing the arctangent function to rapidly achieve SOC balancing of the energy storage units. During the SOC balancing process, as the SOC difference between units decreases, the balancing speed also decreases. To overcome this, a variable acceleration factor is introduced in the arctangent function SOC droop control strategy. This can ensure a progressive increment in the acceleration factor as the SOC gap between energy storage units diminishes. In addition, the integration of DC bus voltage compensation control effectively mitigates voltage deviations within the bus. Finally, the paper presents and simulates a variable acceleration factor-based arctangent function SOC droop control. It demonstrates its effectiveness in achieving SOC balance and maintaining stable bus voltage during charging and discharging scenarios in distributed energy storage systems.

A STANDALONE DC MICROGRID ENERGY MANAGEMENT STRATEGY USING THE BATTERY STATE OF CHARGE

This article introduces an enhanced energy management strategy that employs the state of charge (SoC) of batteries in standalone DC microgrids with photovoltaic (PV) modules. Efficient energy management is crucial to ensure uninterrupted power supply to the load units in microgrids. To address the challenges posed by external factors such as temperature fluctuations and variations in solar irradiance, energy storage systems are deployed to compensate for the negative effects of the external factors on the output power of PV modules. The proposed approach takes into account various parameters of the microgrid elements, including the available power from the sources, demand power, and the SoC of batteries, in order to develop an efficient energy control mechanism with load-shedding capability. By considering these parameters, the strategy aims to optimize the utilization of available resources while ensuring a reliable power supply to the connected loads. The SoC of the batteries plays a critical role in determining optimal charging and discharging profiles, enabling effective energy management within the microgrid. To evaluate the effectiveness of the proposed approach, an algorithm is designed and simulations are conducted. The proposed algorithm utilizes a hybrid approach by combining power and SoC-based methods for efficient control. Through analysis of the simulation results, it is found that the presented approach is capable of delivering the intended load power while increasing the life cycle of the batteries with the pre-defined SoC levels.

Dynamic Distributed Collaborative Control for Equitable Current Distribution and Voltage Recovery in DC Microgrids

In a stand-alone DC microgrid featuring several distributed energy resources (DERs), droop control is adopted to achieve a proportional distribution of current among the DERs within the microgrid. The operation of the droop control mechanism leads to a variation in bus voltage, which is further amplified by the line impedance between the DC bus and DERs. This paper proposes an enhanced distributed secondary control technique aimed at achieving equitable current sharing and voltage regulation simultaneously within a DC microgrid. The proposed distributed secondary control is incorporated into the cyber layer of the microgrid, facilitating the exchange of information among the controllers. In the event of a communication link breakdown, this technique upholds the reliability of the entire system. The control loop utilizes a type-II fuzzy logic control framework for the adaptive selection of the control parameters to improve the control response. Furthermore, the proposed technique can handle both resistive and constant power loads without any particular prerequisites. Utilizing the Lyapunov method, appropriate stability criteria for the proposed controller have been formulated. Various tests were performed across a range of operational scenarios to assess the robustness of the proposed control technique through MATLAB/Simulink® models, which have been validated with real-time experiments. The outcomes revealed that the proposed control effectively achieves its control objectives within a DC microgrid, showcasing rapid responsiveness and minimal oscillation.

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.

Energy coordinated control of DC microgrid integrated incorporating PV, energy storage and EV charging

The power of photovoltaic (PV) and electric vehicles (EV) charging in integrated standalone DC microgrids is uncertain. If no suitable control strategy is adopted, the power variation will significantly fluctuate in DC bus voltage and reduce the system’s stability. This paper investigates the energy coordination control strategy for the standalone DC microgrid integrated with PV, energy storage, and EV charging. The specific research contents include the following: The maximum power point tracking (MPPT) control of the variable-step perturbation observation method is proposed to shorten the regulation time of the PV unit to reach the maximum power point; an improved droop control is designed based on the state of charge (SOC) of the batteries, and the power equalization and bus voltage recovery secondary controls are introduced to enhance the regulation effect of the DC bus voltage; a coordination control strategy based on the power difference is formulated to improve further the transient and steady-state performance of the DC bus voltage. The proposed coordination control strategy is applied to the integrated standalone DC microgrid model built by MATLAB/Simulink. The simulation results show that the proposed coordination control strategy can not only effectively improve the stability of the DC microgrid system but also reduce the capacity redundancy of the energy storage device.

Multi-layer Voltage Control Strategy for DC Microgrid without Communication

This paper presented a multi-layer voltage control strategy for a stand-alone DC Microgrid. The unbalanced power of the system is compensated by the hybrid energy storage. The bus actual voltage is used as a message to implement the coordination of various terminals. By dividing the bus voltage, different voltage layers correspond to different working modes of each terminal of the system. The novelty of the presented control strategy is that the energy management performance of the DC Microgrid is improved, which is independent of the communication link. The DC Microgrid model is established in MATLAB/Simulink environment, and the simulation result shows that the presented strategy is feasible under different setting scenarios.

Battery Lifetime Extension in a Stand-Alone Microgrid With Flexible Power Point Tracking of Photovoltaic System

In stand-alone dc microgrids (dcMGs), battery energy storage systems (BESSs) are conventionally used for regulating the dc-link voltage, causing a continuous battery operation. Though operating the photovoltaic (PV) system at its maximum power point (MPP) yields minimum battery discharge current, the opposite is true for battery charging current. Therefore, reducing the battery charging current based on its state-of-charge (SoC) and the amount of available PV surplus power (which can be treated as virtually stored energy) is an opportunity for improving the battery life. The main objective of the control strategy proposed in this article is to prolong the battery lifetime by reducing the charging current and keeping the battery SoC at lower values if the PV power is enough to supply the loads. Additionally, the PV system is used as the primary asset to regulate the microgrid voltage. The dynamic performance of the proposed control strategy is validated with experimental tests under various operating conditions. Furthermore, its effectiveness in prolonging the battery lifetime is evaluated using an aging model of a lithium-ion (Li-ion) battery (without loss of generality) by simulated case studies.

EXPERIMENTAL ANALYSIS OF HYBRID ENERGY STORAGE SYSTEM BASED ON NONLINEAR CONTROL STRATEGY

In this paper, a nonlinear integral sliding mode control for a hybrid energy storage system (HESS) based stand-alone dc microgrid has been proposed and applied experimentally. This hybrid system comprises a PV, super-capacitor, and battery. A classical PI-based linear control strategy has been designed to control battery and super-capacitor systems based on decoupling the high and low-frequency components to estimate reference current. Since the frequent discharge during operation, super-capacitor power can reach the lowest value, affecting controller performance and making the system unstable. From the experimental result, a nonlinear Integral sliding mode control ISMC is performed as an inner loop controller to regulate battery and super-capacitor power. Also, the PI controller is implemented as an outer loop controller to regulate the dc-link. The proposed control approach is compared with the linear PI controller to improve life extension and minimize stress on the battery. As a result, the proposed control strategy has achieved high dynamic system performance.

Optimum Sizing and Modeling of Stand-Alone DC Microgrid With Hybrid Energy Storage System for Domestic Applications: Cost of Energy, Net Present Cost, and Feasible Configurations

In this article, optimum sizing and modeling of a stand-alone dc microgrid (DCMG) system for domestic applications with hybrid storage system is been proposed. The hybrid storage system consists of a lithium-ion battery (LIB) and supercapacitor (SC). The DCMG is designed to meet the load requirements of a house located in Aruppukottai, in the southern region of Tamil Nadu, India. The daily energy demand is estimated as 7.77 kWh with a peak load of 1.19 kW. This DCMG is designed and simulated by using Homer Pro software. The optimum sizing of solar photovoltaics (PVs), wind turbine (WT), LIB, and SC is evaluated based on cost of energy (CoE) and net present cost (NPC), and all feasible configurations are discussed. The feasible configurations include PV+LIB, PV+WT+LIB, WT+LB, PV+WT+SC, PV+SC, and WT+SC and are compared in terms of CoE and NPC. The results show that the PV+LIB architecture is the optimum configuration, with a CoE of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"><tex-math notation="LaTeX">${\$}$</tex-math></inline-formula> 0.2/kWh and an NPC of $7,334.

Battery Management of Photovoltaic-Based Standalone DC Microgrid for Houses in Rural Areas

DC Microgrids are very popular these days because they can provide qualitative and quantitative energy to remote regions. There is stochastic behaviour and uncertainty in DC microgrids (MG) that use renewable resources. As a result, battery units are required in DC microgrids to assure power balance. Effective coordination and control are necessary for standalone DC MG to accomplish efficient energy management and effective utilization of resources and storage units. A 48V standalone DC MG for remote residences is proposed, consisting of a photovoltaic (PV) system, MPPT, DC/DC boost converters, and storage batteries. Only a few of the challenges include the integration of distributed energy resources (DERs) into DC MG, MPPT, battery charge-discharge control, and voltage deviation control at the DC bus. All of these issues have been considered and investigated in this paper. As a result, the existence of a complete control platform is highly desirable. The entire system is created and tested in the Typhoon Hil environment.

Energy management and control strategy of DC microgrid based hybrid storage system

In this paper, a method of energy management shared with storage devices in a standalone DC microgrid is presented. The objective of management is to satisfy the energy demand in addition to guaranteeing a production/consumption balance with good regulation and stability of DC bus voltage. Another advantage of the energy management method lies in the consideration of losses in the static converters by calculating the effective power available on the common DC bus. The proposed control strategy takes advantage of non-linear control by combining fuzzy logic control for the extraction of the maximum power from the photovoltaic and wind sources, while sliding mode control is used for the control of the storage power converters. The control of the power flow of the common DC bus allowed good stability of the bus voltage with small deviations around the desired value, limiting the battery stress since the low-frequency current component is sent to the battery while the higher-frequency power component is directed to the supercapacitor. The simulation results show the validity of the proposed energy management and control strategy.