A consensus-based robust secondary voltage and frequency control scheme for islanded microgrids

Hu, Junyan; Bhowmick, Parijat

doi:10.1016/j.ijepes.2019.105575

Cited by 68 publications

(32 citation statements)

References 35 publications

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“…The operation of the microgrid with the primary control layer alone, in the islanded mode, causes the steady-state load-dependent frequency and voltage deviations, giving rise to power quality issues and deteriorating the healthy operation of the microgrid. Thus, it needs to compensate for these deviations by the deployment of an additional secondary control layer in order to restore the frequency and voltage of each DER unit back to its nominal (i.e., reference or standard) value [10]- [13].…”

Section: Introductionmentioning

confidence: 99%

“…This controller issues global commands to gather system-wide information, thus requiring a complex and costly communication network, lacking flexibility and prone to single point of failure. That is, the centralized control strategy stops working no matter whether a single node breaks down from or loses connection to the remaining communication network, caused by the communication link failure [13], [22], [23]. Conversely, the main advantage of the distributed control strategy is that a node is not necessarily needed to communicate with all the other nodes in the communication network, thus reducing the cost and bandwidth requirement of the communication network and enhancing the reliability of the overall microgrid operation.…”

Section: Introductionmentioning

confidence: 99%

“…A wide variety of distributed cooperative secondary control strategies can be found in the existing scientific literature. Such as, in [13], a consensus-based robust secondary frequency and voltage restoration along with active power sharing control strategy has been implemented for an islanded AC microgrid based on a prototype IEEE 14-bus system. The proposed strategy has been found superior to distributed cooperative secondary voltage control of microgrids using feedback linearization, reported in [25] by effectively handling frequent switching communication topologies, parametric uncertainties, plug-and-play feature, load disturbances and communication time-delays.…”

Section: Introductionmentioning

confidence: 99%

“…The frequencies, voltage magnitudes, and active/reactive powers of all the DGs were regulated to the desired reference values under both fixed and switching communication network topology with non-uniform timevarying delays. The closed-loop system response becomes oscillatory, or even unstable, when the communication timedelay exceeds a certain extent, as reported in [13], [29]. The idea of distributed-averaging proportional-integral (DAPI) controller has been introduced, in [30], and implemented for secondary frequency and voltage control of islanded AC microgrid, comprising four inverter-interfaced DG units.…”

Section: Introductionmentioning

confidence: 99%

“…2) The proposed control scheme ensures equal active power sharing and frequency regulation using a single control protocol for each DER unit as compared to the concepts reported in [13], [31]- [33], where a separate control methodology has been used for both purposes.…”

Section: Introductionmentioning

confidence: 99%

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Consensus-Based Delay-Tolerant Distributed Secondary Control Strategy for Droop Controlled AC Microgrids

et al. 2021

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This article formulates a fully-distributed and delay-tolerant secondary control scheme for droop-controlled AC microgrids. The proposed strategy is inspired by the cooperative control concept of multi-agent systems (MASs). It considers the hierarchical control structure of the distributed energy resource (DER) units. It ensures equal active power sharing between three DER units, where each unit tracks the time-varying average load, with a finite-time convergence. As a result, the frequencies of the DER units are regulated to their nominal values. Furthermore, it offers plug-and-play capability for DER units, demonstrates significant robustness against load disturbances, and successfully tolerates, small as well as large, communication time-delays. Due to the fully-distributed configuration of the proposed control strategy, each DER unit in the test microgrid requires only its own information and information of its neighbors. The benefit is two-fold: not only this configuration assists in minimizing the overall bandwidth requirement, and cost of the corresponding communication network, but also it increases the reliability of the microgrid operation. The performance and effectiveness of the proposed technique is supported by exhaustive numerical simulations performed in Matlab/Simulink on an AC microgrid testbench comprising three DER units. The proposed strategy renders the superior performance in several aspects as compared to the existing developments in the literature in this area.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Consensus-Based Delay-Tolerant Distributed Secondary Control Strategy for Droop Controlled AC Microgrids

et al. 2021

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Microgrid distributed secondary control and energy management using multi‐agent system

Almada

Leão

Almeida

et al. 2021

Int Trans Electr Energ Syst

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This paper is concerned with the two-stage hierarchical control of microgrids (MG) that can operate in both grid-connected and off-grid modes. The procedure consists in the segmentation of the control scheme in the primary and secondary levels, thus enabling the application of faster and slower dynamics according to the process. A decentralized droop control-based method is used in the primary level, while a distributed multi-agent coordination scheme is applied in the secondary one. The multi-agent system is run on Python Agent DEvelopment (PADE) environment, a FIPA-compliant agent framework. The key contributions this paper provides are the control strategies of reactive power output of nondispatchable sources, dynamic sharing of energy storage systems, and the management of loads of microgrids, all of them based on multi-agent system. Cosimulations using PSCAD TM and PADE are performed considering several operating scenarios of the MG resources under different load conditions. Simulation results validate the accurate performance of the proposed control strategies. K E Y W O R D Sdistributed energy resources, distributed generation, droop control, energy storage system, hierarchical control, microgrid, multi-agent systems List of abbreviations: ω*, frequency for P*; V*, voltage amplitude for Q*; ω, measured frequency; V, measured voltage amplitude; P*, active power reference; Q*, reactive power reference; P, measured active power; Q, measured reactive power; G P (s), active power controller; G Q (s), reactive power controller; m p , proportional gain of active power; m d , derivative gain of active power; m i , integral gain of active power; n p , proportional gain of reactive power; n i , integral gain of reactive power; MOP, MG status; α, coeficiente modifica a potência BT com seu SoC; Δδ, angular difference between the MG and the main network voltages; k, gain for achieve synchronism; f nom and ω nom , nominal frequency [Hz and rad/s]; S nom , rated power; V nom , nominal voltage; Z cable , cable impedance; E max , maximum energy of battery bank; P MPP , optimal instantaneous active power of the nondispatchable source; β, adjustment factor for reactive power; Q max , maximum active power generated by intermittent sources; Q L , reactive power requested by the load; Q int *, reference reactive power for intermittent resources; Q disp *, reference reactive power for dispatchable resources; CX x , the availability of the resource (0 = unavailable, 1 = in operation); nd, number of dispatchable DERs; ni, number of intermittent DERs; ACL, agent communication language; AgDERdisp, agent of dispatchable DER; AgDispG, agent of dispatchable generation; AgESS, agent of ESS; AgIG, agent of intermittent generation; AgIGB, agent of intermittent generation balance; AgL, agent of load; AgPCCandB, agent of pcc and balance; AgTL, agent of total load;

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An efficient distributed approach for aself‐healingsmart grid using minimal spanning tree

Nedjah

Cardoso

Mourelle

2021

Intl J of Energy Research

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In the event of a network failure that compromises energy supply, the characteristic of smart grid self-healing consists of finding a proposal for reconfiguration of the grid, aiming at restoring the power, partially or completely to supply all network nodes. The search for a satisfactory reconfiguration is a combinatorial problem whose complexity is proportional to the network size. An exhaustive search-based method is time-consuming and often computationally non-viable. To overcome this difficulty, techniques for generating minimal spanning trees (MSTs) of the graph that represents the smart grid, are exploited. However, existing studies provide centralized implementations. In this work, we propose a distributed implementation, where each of the network switch collaborates in developing of the recovery solution. The proposed decentralized approach seeks a reduction of reconfiguration time requirements, thus increasing network intelligence. For this purpose, a distributed algorithm for building the MST is embedded in the processing elements available at the commutation nodes. The evaluated case studies show that, whenever possible, the proposed solution allows for a successful reconfiguration, regardless of the number of simultaneous failures. Moreover, the network reconfiguration time is not significantly impacted by the number of buses and included lines. The implementation presents results of communication cost and reconfiguration time significantly lower than the expected upper bounds. Notably, for the case studies, the proposed implementation achieves 70% and 69% speedup regarding the reconfiguration time from simple and multiple failures, respectively, when compared to the expected theoretical performance. Furthermore, when compared to existing multiagentbased self-healing systems, the proposed implementation recovers from failures twice as fast, making it more desirable in a smart-grid real implementation.

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A consensus-based robust secondary voltage and frequency control scheme for islanded microgrids

Cited by 68 publications

References 35 publications

Consensus-Based Delay-Tolerant Distributed Secondary Control Strategy for Droop Controlled AC Microgrids

Consensus-Based Delay-Tolerant Distributed Secondary Control Strategy for Droop Controlled AC Microgrids

Microgrid distributed secondary control and energy management using multi‐agent system

An efficient distributed approach for aself‐healingsmart grid using minimal spanning tree

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