Robust Sliding Mode and Mixed $H_2$/$H_\infty$ Output Feedback Primary Control of AC Microgrids

Raeispour, Mohammad; Atrianfar, Hajar; Baghaee, Hamid Reza; Gharehpetian, Gevork B.

doi:10.1109/jsyst.2020.2999553

Cited by 36 publications

(13 citation statements)

References 37 publications

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“…However, MGC control has received more attention recently due to increasing interest in the MGC concept. According to the researches, the MGC control strategy can be categorized as master-slave [35][36][37], peer-to-peer (P2P) [38][39][40], and hierarchical control [41][42][43].…”

Section: Control Strategiesmentioning

confidence: 99%

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A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids

et al. 2022

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Section: Control Strategiesmentioning

confidence: 99%

“…The V/f control method, in comparison with droop control, suffers from a slow dynamic response [45]. The main disadvantage of master-slave control is the reliability dependency of the whole system to the master converter and consequently interruption of the whole system in case of master converter failure [35].…”

Section: Control Strategiesmentioning

confidence: 99%

A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids

et al. 2022

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“…Optimal power sharing amongst DERs is another challenge in an NMG. The control of single MGs was discussed in several articles [31][32][33][34][35][36]. However, control in NMGs has recently become the focus because of the increasing interest in NMG research.…”

Section: Control In Nmgsmentioning

confidence: 99%

Control and optimisation of networked microgrids: A review

Islam

Yang

Ամին

2021

IET Renewable Power Gen

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Microgrids (MGs) have become an integral part of smart grid initiatives for future power system networks. Networked microgrids consist of several neighbouring microgrids connected in a low/medium distribution network. The primary objective of a network is to share surplus/shortage power with neighbouring microgrids to achieve mutual cost‐effective operation, utilising green energy from renewable energy resources in the network and increasing the reliability of customer service. This article classifies networked microgrids on the basis of network formation and provides an overview of recent research on control of networked microgrids. In addition, a state‐of‐the‐art review of optimisation methods is provided to solve the energy optimisation problem in networked microgrids. Furthermore, the advantages and challenges of the networked operation of microgrids are presented as for possible research directions in the future.

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“…Once the control synthesis problem is formulated using a semidefinite program involving LMIs, it can be numerically solved with standard optimization algorithms [20]. In the context of DER units within microgrid systems, the use of LMIs for control design purposes has been previously considered in [21]- [28], among others. However, in general, the control strategies assume a PLL algorithm for synchronization and orientation purposes, or they are cascade control structures conceived for a specific mode of operation; islanded or grid-connected.…”

Section: Introductionmentioning

confidence: 99%

Dynamic Output-Feedback Decentralized Control Synthesis for Integration of Distributed Energy Resources in AC Microgrids

Pérez-Ibacache

Castro

Pimentel

et al. 2022

IEEE Trans. Smart Grid

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This work proposes a control design procedure based on Linear Matrix Inequalities (LMI) for integrating Distributed Energy Resources (DERs) in microgrid systems. Each DER uses local measurements as feedback, so this proposal results in a method to design a decentralized primary control. The dynamic model employed to synthesize such a controller presents an unmeasured state vector, model uncertainties, and random disturbances. To simultaneously deal with all these difficulties while ensuring the closed-loop stability and multiple performance specifications, this work is formulated in terms of a single Lyapunov function. To find this Lyapunov function and synthesize the controller gains, a convex optimization problem that involves LMIs is required to be solved. The controller results in a linear discrete-time output-feedback form, facilitating its implementation. The time-domain simulation of a microgrid system is performed in the software PSCAD/EMTDC with four DERs to validate the control design procedure's effectiveness.

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Robust Sliding Mode and Mixed $H_2$/$H_\infty$ Output Feedback Primary Control of AC Microgrids

Cited by 36 publications

References 37 publications

A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids

A Comprehensive Review of Control Strategies and Optimization Methods for Individual and Community Microgrids

Control and optimisation of networked microgrids: A review

Dynamic Output-Feedback Decentralized Control Synthesis for Integration of Distributed Energy Resources in AC Microgrids

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