Leader–Follower-Based Distributed Secondary Voltage Control for a Stand-alone PV and Wind-Integrated DC Microgrid System with EVs

Bhargavi, K. M.; Jayalakshmi, N. S.

doi:10.1007/s40313-019-00530-6

Cited by 9 publications

(4 citation statements)

References 30 publications

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“…hence, the voltage and current output derivatives of the ith DER in reference to the control signal generated by the distributed secondary control can be computed from (31) as follows:…”

Section: Stability Analysismentioning

confidence: 99%

“…The effect of DER plug-and-play was also not considered. In [31], a distributed linear multi-agent consensus protocol was utilized to develop a leader-follower consensus algorithm for the secondary layer of multiple battery energy storage units to achieve voltage control and balanced power distribution, while a distributed voltage observer was proposed in [32] for a similar DC microgrid. The drawback of the posited leader-follower algorithm is the substantial deviation in the bus voltage when the leader breaks down.…”

Section: Introductionmentioning

confidence: 99%

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

Lasabi,

Swanson,

Jarvis

et al. 2023

Energies

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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.

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“…hence, the voltage and current output derivatives of the ith DER in reference to the control signal generated by the distributed secondary control can be computed from (31) as follows:…”

Section: Stability Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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

Lasabi,

Swanson,

Jarvis

et al. 2023

Energies

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show abstract

“…In the DC microgrid power flow, nodes can be divided into two types [13]. In this study, they are defined as W nodes and Q nodes, where the node power equation of Q node is…”

Section: Power Flow Calculationmentioning

confidence: 99%

Hierarchical Coordinated Control of DC Microgrid Based on Recursive Fuzzy Neural Network Algorithm

Wang

Liu

et al. 2022

Wireless Communications and Mobile Computing

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In order to realize the stable operation of the DC microgrid, a hierarchical coordinated control method of the DC microgrid based on the recursive fuzzy neural network algorithm is designed in this article. Based on the analysis of the working mode and topology of the DC microgrid, the droop control coefficient is calculated through power flow calculation, and then, a three-layer control strategy is designed combined with a hierarchical coordinated control algorithm to realize the distributed coordinated control of DC microgrid. Combined with the recursive fuzzy neural network algorithm, the real-time amplitude limiting and convergence of the output of the distributed coordination controller are realized. Experimental results show that under the control of this method, the changes in current and voltage at each port of the DC microgrid are relatively stable during off-grid switching. In addition, this method effectively reduces the fault rate of power grid lines, which fully proves the feasibility and reliability of this method.

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“…With the absence of droop in the 1 0 ry control loops of the distributed generators, the failure of any of the 2 0 ry controllers will exacerbate the voltage and current-sharing deviation in the µgrid. In [43], a leader-follower consensus algorithm based on distributed linear multiagent consensus protocol is developed for the 2 0 ry control layer of multiple battery energy storage units in DC µgrid to achieve balanced power-sharing and voltage control. The limitation of the posited leader-follower algorithm is the large deviation in the voltage of the DC bus when the leader fails.…”

Section: Introductionmentioning

confidence: 99%

A Distributed Control Scheme for Cyber-Physical DC Microgrid Systems

et al. 2023

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An innovative distributed secondary control technique for balanced current sharing and voltage regulation for an off-grid DC microgrid setup is presented in this research. The droop control scheme is conventionally used for current sharing amongst distributed sources (DSs) in a microgrid. However, this method has two major drawbacks. Firstly, due to the line resistance of each DS, the output voltage is different for each DS, and the output current-sharing property deteriorates. Secondly, the droop action increases the DC bus voltage variation. To address these drawbacks, a fuzzy-based distributed secondary controller is proposed. The proposed controller in each DS simultaneously ensures balanced current sharing and sustains DC bus voltage at the reference value by using a communication network to interact with one another. The required circumstance to guarantee the proposed controller’s stability is provided. The stability analysis is beneficial to inform the choice of control parameters. The real-time simulation outputs demonstrate the proposed control scheme’s robustness in achieving the control objectives under varying operating conditions.

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Leader–Follower-Based Distributed Secondary Voltage Control for a Stand-alone PV and Wind-Integrated DC Microgrid System with EVs

Cited by 9 publications

References 30 publications

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

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

Hierarchical Coordinated Control of DC Microgrid Based on Recursive Fuzzy Neural Network Algorithm

A Distributed Control Scheme for Cyber-Physical DC Microgrid Systems

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