Adaptive Master-Slave Control Strategy for Medium Voltage DC Distribution Systems Based on a Novel Nonlinear Droop Controller

Xie, Xingfeng; Quan, Xiangjun; Wu, Zheng-Mao; Cao, Xiaoyong; Dou, Xiaobo; Hu, Qinran

doi:10.1109/tsg.2021.3104413

Cited by 20 publications

(8 citation statements)

References 31 publications

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“…The structure of the microgrid, such as the terminal can be different based on the application scenarios. Generally, the energy management of the microgrid can be categorized into three types: hierarchical control Zhao et al (2016), autonomous control Pogaku et al (2007), and master-slave control Xie et al (2021). The power flow control of the microgrid is conducted via changing the operating modes of the power 10.3389/fenrg.2023.1334588 converters.…”

Section: Related Workmentioning

confidence: 99%

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

Xu,

Zhang,

Bai

et al. 2024

Front. Energy Res.

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Microgrid has been extensively applied in the modern power system as a supplementary mode for the distributed energy resources. The microgrid with wind energy is usually vulnerable to the intermittence and uncertainty of the wind energy. To increase the robustness of the microgrid, the energy storage system (ESS) is necessary to compensate the power imbalance between the power supply and the load. To further maximize the economic efficiency of the system, the system level control for the microgrid is desired to be optimized when it is integrated with the utility grid. Aiming at the aforementioned problem, this paper comprehensively analyzes the power flow of a typical loop microgrid. A transformer-based wind power prediction (WPP) algorithm is proposed and compared with recurrent neural networks algorithm. With the historical weather data, it can accurately predict the 24 h average wind energy. Based on the predicted wind energy and the time-of-use (TOU) electricity price, a day-ahead daily cycling profile of the ESS with particle swarm optimization algorithm is introduced. It comprehensively considers the system capacity constraints and the battery degree of health. The functionality of the proposed energy management strategy is validated from three levels. First, WPP is conducted with the proposed algorithm and the true historical weather data. It has validated the accuracy of the transformer algorithm in prediction of the hourly level wind energy. Second, with the predicted wind energy, a case study is given to validate the day-ahead daily cycling profile. A typical 1 MVA microgrid is utilized as the simulation model to validate performance of the daily cycling optimization algorithm. The case study results show that the ESS daily cycling can effectively reduce the daily energy expense and help to shave the peak power demand in the grid.

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Section: Related Workmentioning

confidence: 99%

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

Xu,

Zhang,

Bai

et al. 2024

Front. Energy Res.

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“…Onshore MMCs provide greater flexibility in importing power into the DC connection, demanding coordinated measures to avoid power imbalances during outages. Furthermore, the author in [70] offers a unique nonlinear droop (ND) controller-based adaptive master-slave (AMS) control technique. One master station and multiple slave stations with ND control compose the AMS system.…”

Section: Master Slave With Droop Controlmentioning

confidence: 99%

Power Sharing Control Trends, Challenges, and Solutions in Multi-Terminal HVDC Systems: A Comprehensive Survey

Alrajhi,

Daraz,

Alzahrani

et al. 2024

IEEE Access

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This extensive review article provides a comprehensive analysis of control strategies for power sharing in Multi-Terminal High Voltage Direct Current (MT-HVDC) systems utilizing voltage source converters (VSC) and multi-level modular converters (MMC). MT-HVDC systems have become essential components of modern power infrastructures due to their ability to efficiently transmit energy over long distances, connect renewable energy sources, and enhance grid stability. Effective power sharing control is of uttermost importance in these systems for ensuring equitable energy distribution between terminals and grid reliability. The paper begins with a thorough explanation of the fundamental concepts underlying MT-HVDC systems, emphasizing their significance, and examining the various configurations of such systems. The discussion then examines the functions of VSCs and MMCs in these systems, highlighting their distinct advantages and applications. The review analyses in depth the complex power sharing control strategies within VSC-based and MMC-based multi-terminal HVDC systems, as well as a number of control methods, algorithms, and optimization techniques. In addition, the article discusses difficulties and solutions associated with power sharing control in MT-HVDC systems, such as communication and synchronization issues.INDEX TERMS Cascaded controller, DC systems, High voltage direct current (HVDC), modular multilevel converter (MMC) multi-terminal HVDC, Power Control Sharing, Voltage source converter (VSC).

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“…Therefore, appropriate control strategies of all units including MMCs should be properly selected to ensure the stability of DC bus voltage. Master-slave (M-S) control, as a typical coordinated control strategy (Xie et al, 2021), is adopted in this system. The master converter adopts constant voltage control to stabilize the DC bus voltage.…”

Section: Mvdc-ds Operation Modementioning

confidence: 99%

An improved energy management for MVDC distribution system based on exponential droop control

et al. 2022

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The energy management optimization and DC voltage stability are the main challenges when loads surging and renewable energy sources (RESs) fluctuations occur in the medium-voltage DC distribution system (MVDC-DS). To solve these issues, this paper proposes a dual-time scale energy management method based on improved droop control for the MVDC-DS. Firstly, a ±10 kV three-terminal hybrid modular multilevel converter (MMC)-based ring MVDC-DS with DC fault ride-through capability is constructed, which including electric vehicle charging stations, energy storage systems, multiple loads and RESs. Secondly, the droop control adopted by the hybrid MMC is improved by exp-function to achieve higher power quality. On this basis, a dual-time scale energy management method is proposed to minimize the electricity purchasing cost. The reference power of each controllable unit is optimized in the long time scale, and the parameters of improved droop control are optimized in the short time scale. Finally, a case study is conducted on the ±10 kV three-terminal hybrid MMC-based ring MVDC-DS, and the results indicate that the proposed method can improve the economy and power quality of system, and help to realize the normal system operation under different conditions.

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Adaptive Master-Slave Control Strategy for Medium Voltage DC Distribution Systems Based on a Novel Nonlinear Droop Controller

Cited by 20 publications

References 31 publications

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

The energy management strategy of a loop microgrid with wind energy prediction and energy storage system day-ahead optimization

Power Sharing Control Trends, Challenges, and Solutions in Multi-Terminal HVDC Systems: A Comprehensive Survey

An improved energy management for MVDC distribution system based on exponential droop control

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