Review on Control of DC Microgrids

Meng, Lexuan; Shafiee, Qobad; Trecate, Giancarlo Ferrari; Karimi, Houshang; Fulwani, Deepak; Liu, Xiaonan; Guerrero, Josep M.

doi:10.1109/jestpe.2017.2690219

Cited by 360 publications

(102 citation statements)

References 185 publications

(225 reference statements)

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“…A number of robust networked control systems for DC MGs have emerged recently [13]. Besides the standard, centralized approach that is inherited from large-scale power systems, a distributed control implemented by multiple agents is a viable solution that mitigates the single-point-of-failure problem and increases the system modularity [1]. The distributed control is typically based on consensus algorithm, which permits the agents to converge to a global average using only the information exchanges that are performed among, in communication terms, neighboring agents [14], [5], [15].…”

Section: Background and Motivationmentioning

confidence: 99%

Software-Defined Microgrid Control for Resilience Against Denial-of-Service Attacks

Danzi

Angjelichinoski

Stefanović

et al. 2019

IEEE Trans. Smart Grid

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Microgrids (MGs) rely on networked control supported by off-the-shelf wireless communications. This makes them vulnerable to cyber-attacks, such as denial-of-service (DoS). In this paper, we mitigate those attacks by applying the concepts of (i) separation of data plane from network control plane, inspired by the software defined networking (SDN) paradigm, and (ii) agile reconfiguration of the data plane connections. In our architecture, all generators operate as either voltage regulators (active agents), or current sources (passive agents), with their operating mode being locally determined, according the global information on the MG state. The software-defined MG control utilizes the fact that, besides the data exchange on the wireless channel, the power-grid bus can be used to create side communication channels that carry control plane information about the state of the MG. For this purpose, we adopt power talk, a modem-less, low-rate, power-line communication designed for direct current (DC) MGs. The results show that the proposed software-defined MG offers superior performance compared to the static MG, as well as resilience against cyber attacks.The cooperation among agents is supported by an external communication network, which can experience delay and packet loss, thereby deteriorating the MG operation. With non-ideal links, the secondary/tertiary control operate in a suboptimal regime. A possible solution is the adoption of robust control schemes that are tolerant against communication delays and/or packet drops, cf. [5]. However, when the communication network is attacked by e.g. Denial of Service (DoS), the secondary/tertiary control fails [6]. In addition to the poor adaptation to communication impairments, another deficiency of existing MG control is the information security: the increase of the number of attacks against big-scale power systems raises a concern also about the cyber-resilience of the small scale grids. In fact, even if the MG failure does not lead to large blackouts, it may damage sensitive loads, such as electronic equipment, or cause the tripping of DERs [7].

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Section: Background and Motivationmentioning

confidence: 99%

Software-Defined Microgrid Control for Resilience Against Denial-of-Service Attacks

Danzi

Angjelichinoski

Stefanović

et al. 2019

IEEE Trans. Smart Grid

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“…Microgrid clusters (MGC), which consist of multiple MGs, have received considerable attention recently [21][22][23][24]. The essence and goal of the MGC is to increase the penetration ratio of MG in the conventional distribution network, achieve the efficient and stable operation of the renewable energy, and friendly interaction with the grid [25].…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the MGC can be utilized to cope with the distributed coordination issues, while guarantees the stable operation of the system. Fig.2 The structrue of microgrid cluster (MGC) [21,25,27].…”

Section: Introductionmentioning

confidence: 99%

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

Han

Zhang

et al. 2018

IEEE Trans. Power Electron.

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366

182

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Abstract-The increasing integration of the distributed renewable energy sources highlights the requirement to design various control strategies for microgrids (MGs) and microgrid clusters (MGCs). The multi-agent system (MAS)-based distributed coordinated control strategies shows the benefits to balance the power and energy, stabilize voltage and frequency, achieve economic and coordinated operation among the MGs and MGCs. However, the complex and diverse combinations of distributed generations in multi-agent system increase the complexity of system control and operation. In order to design the optimized configuration and control strategy using MAS, the topology models and mathematic models such as the graph topology model, non-cooperative game model, the genetic algorithm and particle swarm optimization algorithm are summarized. The merits and drawbacks of these control methods are compared. Moreover, since the consensus is a vital problem in the complex dynamical systems, the distributed MAS-based consensus protocols are systematically reviewed. NOMENCLATURE

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“…Microgrids can operate in a low or medium voltage range and generate their own power, that is, renewable sources along with energy storage, nonrenewable sources, and power electronic (PE) controlled loads [1]. The unique property of microgrids is that they can work in islanded mode under faulty conditions, which increases the reliability of the power supply [2][3][4]. In AC microgrids, the distribution system is AC.…”

Section: Introductionmentioning

confidence: 99%

Proportional Load Sharing and Stability of DC Microgrid with Distributed Architecture Using SM Controller

Rashad

Raoof

Ashraf

et al. 2018

Mathematical Problems in Engineering

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DC microgrids look attractive in distribution systems due to their high reliability, high efficiency, and easy integration with renewable energy sources. The key objectives of the DC microgrid include proportional load sharing and precise voltage regulation. Droop controllers are based on decentralized control architectures which are not effective in achieving these objectives simultaneously due to the voltage error and load power variation. A centralized controller can achieve these objectives using a high speed communication link. However, it loses reliability due to the single point failure. Additionally, these controllers are realized through proportional integral (PI) controllers which cannot ensure load sharing and stability in all operating conditions. To address limitations, a distributed architecture using sliding mode (SM) controller utilizing low bandwidth communication is proposed for DC microgrids in this paper. The main advantages are high reliability, load power sharing, and precise voltage regulation. Further, the SM controller shows high robustness, fast dynamic response, and good stability for large load variations. To analyze the stability and dynamic performance, a system model is developed and its transversality, reachability, and equivalent control conditions are verified. Furthermore, the dynamic behavior of the modeled system is investigated for underdamped and critically damped responses. Detailed simulations are carried out to show the effectiveness of the proposed controller.

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Review on Control of DC Microgrids

Cited by 360 publications

References 185 publications

Software-Defined Microgrid Control for Resilience Against Denial-of-Service Attacks

Software-Defined Microgrid Control for Resilience Against Denial-of-Service Attacks

MAS-Based Distributed Coordinated Control and Optimization in Microgrid and Microgrid Clusters: A Comprehensive Overview

Proportional Load Sharing and Stability of DC Microgrid with Distributed Architecture Using SM Controller

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