Power Management In DC Microgrids Research Articles

Renewable Energy-Based DC Microgrid with Hybrid Energy Management System Supporting Electric Vehicle Charging System

Growing Electric vehicle (EV) ownership leads to an increase in charging stations, which raises load demand and causes grid outages during peak hours. Microgrids can significantly resolve these issues in the electrical distribution system by implementing an effective energy management approach. The suggested hybrid optimization approach aims to provide constant power regardless of the generation discrepancy and should prevent the early deterioration of the storage devices. This study suggests using a dynamic control system based on the Fuzzy-Sparrow Search Algorithm (SSA) to provide a reliable power balance for microgrid (MG) operation. The proposed DC microgrid integrating renewable energy sources (RES) and battery storage system (BSS) as sources are designed and evaluated, and the findings are further validated using MATLAB Simulink simulation. In comparing the hybrid SSA strategy with the most widely used Particle Swarm Optimization (PSO)-based power management, it was observed that the hybrid SSA approach was superior in terms of convergence speed and stability. The effectiveness of the given energy management system is evaluated using two distinct modes, the variation of solar irradiation and the variation of battery state of charge, ensuring the microgrid’s cost-effective operation. The enhanced response characteristics indicate that the Fuzzy-SSA can optimise power management of the DC microgrid, making better use of energy resources. These results show the relevance of algorithm configuration for cost-effective power management in DC microgrids, as it saves approximately 7.776% in electricity expenses over a year compared to PSO.

Power Management in DC Microgrid by the DC-DC Converters

Abstract: DC loads have proliferated rapidly on the market today and DC micro grids with renewable energies are being built as a potential solution to meet the rising demand for electricity. As different energy sources such as solar, wind, fuel cell, and diesel generators can be incorporated into the DC grid, it is important to control the power flow between the sources. An attempt is made in this paper to study the hybrid system consisting a three energy sources, namely wind energy, photovoltaic power source and Battery. Each of the three energy sources is controlled so as to deliver uninterrupted power supply to the load. A control strategy for the management of power flows with solar and wind energy sources in DC micro grid are discussed. Given that voltage profile regulation is critical in a standalone system, a dedicated converter should be used to maintain the voltage of the DC connection. The battery circuit regulates DC charging voltage, while the full power is derived from Solar and Wind to power the attached DC bus charges. An algorithm is developed to manage power flow between three outlets. The algorithm is evaluated in MATLAB / SIMULINK environments for different charging conditions and variations in solar and wind energy.

A nonlinear double‐integral sliding mode controller design for hybrid energy storage systems and solar photovoltaic units to enhance the power management in DC microgrids

In this paper, a nonlinear decentralized double-integral sliding mode controller (DI-SMC) is designed along with an energy management system (EMS) for the DC microgrid (DCMG). This DCMG includes having a hybrid energy storage system (HESS) that incorporates a battery energy storage system (BESS) and supercapacitor energy storage system (SCESS) while the load demand is met through the power generated from solar photovoltaic (SPV) units. First, dynamical models of each subsystem of DCMGs such as the SPV system, BESS, and SCESS are developed to capture highly nonlinear behaviors of DCMGs under various operating conditions. The proposed nonlinear DI-SMC is then designed for each power unit in DCMGs to ensure the desired voltage level at the common DC-bus and appropriate power dispatch of different components to fulfill the load requirement of the DCMG. On the other hand, an energy management system (EMS) is designed to determine the set point for the controller with an aim of ensuring the power balance within DCMGs under various operating conditions where the overall stability is assessed using the Lyapunov theory. Simulation studies along with the processor-in-loop validation, including a comparative study with a proportional-integral (PI) controller, verify the applicability and effectiveness of the EMS-based DI-SMC under different operating conditions of the DCMG.

Cooperative control strategy for voltage restoration and power allocation in DC microgrids

This paper proposes a novel cooperative control strategy for voltage restoration and power management in DC microgrids based on the DC bus signaling (DBS) method. In the conventional DBS method, the operation mode is determined according to the voltage deviation. Thus, it is difficult to achieve voltage restoration. To overcome this problem, the conventional DBS method is modified by applying the total power of dispatchable units (DUs) to identify the operation mode instead of the voltage deviation. As a result, the average output voltage of the DUs is restored to its nominal value in all of the operation modes without difficulty. In addition, accurate power sharing is achieved regardless of the line impedance or load change by regulating the voltage magnitude using a simple PI controller. Furthermore, the control performance is theoretically analyzed using a small signal analysis to evaluate the stability of system. The proposed method is validated with results from a lab scale experiment.

An Adaptive Approach for Effective Power Management in DC Microgrid Based on Virtual Generation in Distributed Energy Sources

This paper proposes a new control algorithm for effective power management in the dc microgrid with renewable energy sources (RES) and energy storage system (ESS). This scheme overcomes the average power sharing and bus voltage regulation problems with maximum utilization of source power. In the source, the additional power available beyond its average rated value is treated as virtual generation. The new references are generated considering virtual generation. The novelty of the proposed algorithm is to bring the virtual generation effectively in operation. The virtual generation of the individual source is based on available power source. The proposed algorithm reduces the charging/discharging cycles of ESS and, hence, enhances the life span of ESS. It reduces the stress on interfaced converters, regulates the system bus voltage, reduces power fluctuations on the sources, and enhances stability. The proposed control algorithm is verified in MATLAB simulation and in real-time simulator.

Simulation Study of Power Management for a Highly Reliable Distribution System using a Triple Active Bridge Converter in a DC Microgrid

Owing to the acute energy shortage issue and the increasing energy demands of information and communication technology systems worldwide, the development of a DC microgrid that can utilize renewable energy sources, such as wind and photovoltaic power, has been accelerated. Therefore, power management for DC microgrid distributed systems is promoted to achieve high reliability and efficiency in power distribution systems. For industry and power transmission applications such as data centers, power management with the help of DC converters is highly recommended. In this paper, we propose a prototype of a power distribution system with a triple active bridge (TAB) converter for data centers in the DC microgrid. Moreover, we introduce a power management approach for a distribution system using the TAB converter. Finally, we perform simulations of the proposed configuration to verify the controllability of the circuit performance and the high reliability of the system.

Optimal Power Management in DC Microgrids With Applications to Dual-Source Trolleybus Systems

This paper investigates optimal power management in dc microgrids, with its applications to dc dual-source trolleybus systems. High mobility of buses and their impact on power supply networks introduce challenging power management issues. This paper incorporates line power losses in power management strategies and introduces a new distributed optimal power management methodology. A multi-objective optimization model is developed. Using only neighborhood information exchange among feeder lines in the network, the new consensus-type control accommodates both feeder current allocation and power loss reduction with fast convergence. One critical finding of this paper is that our local recursive optimization algorithms achieve the global optimal solution asymptotically. Under random noise on information exchange, convergence and optimality of the proposed method are established rigorously. The power system configurations of the Beijing dual-source trolleybus system are used for simulation case studies on the new power management methods. Feasibility, accuracy, and comparison with global optimization results are demonstrated.

Economic Droop Scheme for Decentralized Power Management in DC Microgrids

Economic Droop Scheme for Decentralized Power Management in DC Microgrids

Multiagent Supervisory Control for Power Management in DC Microgrids

This paper proposes multiagent supervisory control for precise power management in isolated dc microgrids. Two power management aspects are considered: 1) equal power sharing, which is realized via a proposed distributed equal power sharing algorithm; and 2) optimal power dispatch, which is achieved through a proposed distributed equal incremental cost (DEIC) algorithm. Both algorithms offer the additional advantage of the ability to restore the average system voltage to its nominal value. The proposed algorithms are based on the application of the average consensus theory along with voltage sensitivity analysis. Each distributed generation (DG) unit exchanges information with its neighbors, thus locally updating its no-load voltage setting to achieve the supervisory control objectives. The incorporation of DG droop-based control renders the proposed algorithms fully distributed with a reduced number of agents. The stability of the proposed algorithms is addressed, as well as the convergence of the proposed DEIC algorithm. Real-time OPAL-RT simulations demonstrate the effectiveness of the proposed algorithms in a hardware-in-the-loop application.

Power Management for DC Microgrid Enabled by Solid-State Transformer

A novel distributed power management scheme is proposed in this paper for a DC microgrid system, which is enabled by Solid-State transformer (SST). The proposed system includes distributed renewable energy resource (DRER) and distributed energy storage device (DESD). The proposed distributed control algorithm, which only relies on the local information and guarantees full utilization of each module in the system based on their characteristics, is applied to both SST and DC microgrid. To this end, a simulation platform is developed in MATLAB/Simulink, in which Photovoltaic (PV), fuel cell and battery are selected as the typical DRERs and DESD, respectively. Lastly, several typical case studies are carried out and the simulation results verify the proposed distributed power management.