An adaptive nonlinear droop control for accurate load current sharing and DC bus voltage compensation in a DC power system

Tian, Xiaoqing; Wang, Yubin; Wang, Fan; Guo, Zhi

doi:10.1007/s43236-021-00350-5

Cited by 3 publications

(5 citation statements)

References 29 publications

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“…Large signal stability optimization [29,30] Economical optimization [26,36] Operation index deviation optimization [19,20] On the scale of single DCMG Small signal stability optimization [34] Large signal stability optimization [31] Economical optimization [9-11, 22, 28, 32] Operation index deviation optimization [9,24,28,32] been deployed to optimize parameters at the scale of the single DCMG.…”

Section: On the Scale Of The Dcmg Cluster Systemmentioning

confidence: 99%

“…In optimization processing, some approaches combine multiple optimization objectives into a single objective [4,28]. There are numerous issues with this target processing method.…”

Section: On the Scale Of The Dcmg Cluster Systemmentioning

confidence: 99%

“…When there are multiple pairs of conjugate negative numbers, several second-order systems can be connected in series instead of the higher-order system for analysis. OF 2 represents the overall damping ratio of the system, as shown in Equation (28).…”

Section: Optimization Objectivesmentioning

confidence: 99%

“…For example, literature [26] optimizes the droop coefficient and rated voltage to achieve the goal of optimizing system operation. Literature [11,13,27,28] adopts a non-linear droop control method to achieve the goal of improving load sharing, voltage regulation, system efficiency, and other operating indicators. The aforementioned studies on droop-controlled DCMG clusters generally do not emphasize stability improvement but rather validate the stability of the proposed operation mode.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Small signal stability analysis and control parameter optimization of DC microgrid cluster

Zhang,

Yang,

Zhao

et al. 2024

IET Power Electronics

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Direct current microgrid (DCMG) clusters are gaining popularity in power systems due to their simplicity and high efficiency. However, DCMG clusters are susceptible to minor disturbances due to low system inertia. This paper proposes a method to enhance the small‐signal stability of a DCMG cluster by optimizing the main control parameters of the system. This paper presents a small‐signal state‐space model of a DCMG cluster system at the system level, considering a multi‐bus network topology. Then, the control parameters that significantly affect the small‐signal stability of the DCMG are selected using the participation factor method. To enhance the system damping, the Pareto‐optimal frontier of the bi‐objective problem was determined using the elite non‐dominated sorting genetic algorithm (NSGA‐II). The optimal compromise is determined by using the fuzzy membership function method to extract it from the generated Pareto optimal front. The proposed method has been verified on a three‐sub DCMG test system with droop control.

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Section: On the Scale Of The Dcmg Cluster Systemmentioning

confidence: 99%

“…In optimization processing, some approaches combine multiple optimization objectives into a single objective [4,28]. There are numerous issues with this target processing method.…”

Section: On the Scale Of The Dcmg Cluster Systemmentioning

confidence: 99%

Section: Optimization Objectivesmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Small signal stability analysis and control parameter optimization of DC microgrid cluster

Zhang,

Yang,

Zhao

et al. 2024

IET Power Electronics

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“…However, the higher value of droop parameter leads to increased permanent DC voltage deviation on the DC power line. [15,16]…”

Section: Decentralized Control Strategiesmentioning

confidence: 99%

Control Concepts for a Decentralized Battery Management System to Optimize Reliability and Battery Operation

Reindl¹,

Eriksson²,

Niemetz³

et al. 2023

Atlantis Highlights in Engineering

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Battery systems are used in a wide range of safety-relevant applications, such as electric vehicles, unmanned aerial vehicles and home storage systems. Safety, reliability and availability of the battery system therefore play a key role. In addition, the useful service lifetime of the batteries determines the environmental impact and economic efficiency of the overall system. One possible solution is to give batteries a second life in applications with lower requirements in terms of dynamic behavior or capacity. Heterogeneous battery systems consist of batteries with differences in cell technology, age, capacity, and optimal operating range. To meet the safety, reliability, and availability requirements a scalable, Decentralized Battery Management System (DBMS) based on a distributed control system is proposed. Batteries, generators, and loads have Local Control Units (LCUs) consisting of a microcontroller, a measurement unit, and a DC/DC converter with adjustable voltage and current limits. These LCUs are the basis for the communication-based, cooperative system control and enhance the reliability and scalability of the battery system compared to conventional centralized structures. They record and manage the operating parameters and provide the basis for predictive energy management and battery residual value estimation. As a fallback strategy, a droop-based control of the DC/DC converters is used in addition to the communication-based one. Transition conditions between the control modes are defined and the control methods are compared and differentiated. The performance and the resulting benefits of batteries are determined by the control strategies. In this paper, the requirements for the control strategies for different operating modes, including startup, severe fluctuations of the DC power line voltage, and safe shutdown, are analyzed. Keywords:Renewable energy sources • battery management system • second life battery • decentralized control • distributed control • control strategies • droop control • battery optimal operation

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An Improved SoC Balancing Strategy for Battery Energy Storage System in All-Electric Propulsion Ships Current Sharing Effect

Zhang

Liu

et al. 2022

J. Electr. Eng. Technol.

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An adaptive nonlinear droop control for accurate load current sharing and DC bus voltage compensation in a DC power system

Cited by 3 publications

References 29 publications

Small signal stability analysis and control parameter optimization of DC microgrid cluster

Small signal stability analysis and control parameter optimization of DC microgrid cluster

Control Concepts for a Decentralized Battery Management System to Optimize Reliability and Battery Operation

An Improved SoC Balancing Strategy for Battery Energy Storage System in All-Electric Propulsion Ships Current Sharing Effect

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