Decentralized coordinated control for large power system based on transient stability assessment

Dou, Chunxia; Yang, Jinzhao; Li, Yong; Gui, Ting; Bi, Ye-fei

doi:10.1016/j.ijepes.2012.10.035

Cited by 28 publications

(23 citation statements)

References 23 publications

(20 reference statements)

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“…However, this simple approach reduces the controller capability and even leads to stability problems [6]. Considering this, a few of decentralized coordinated control strategies of power system have been proposed [7][8][9][10][11]. A hierarchical decentralized coordinated control strategy is proposed to control the excitation system of synchronous generator (SG), where the interaction terms are considered as bounded disturbances which are suppressed by a ∞ controller [8].…”

Section: Introductionmentioning

confidence: 99%

“…Considering this, a few of decentralized coordinated control strategies of power system have been proposed [7][8][9][10][11]. A hierarchical decentralized coordinated control strategy is proposed to control the excitation system of synchronous generator (SG), where the interaction terms are considered as bounded disturbances which are suppressed by a ∞ controller [8]. A direct feedback linearization based decentralized coordinated control of excitation and steam valve is proposed, where the upper bound of interaction terms is estimated [9].…”

Section: Introductionmentioning

confidence: 99%

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Neural Adaptive Decentralized Coordinated Control with Fault-Tolerant Capability for DFIGs under Stochastic Disturbances

Zhang

Cao

et al. 2017

Mathematical Problems in Engineering

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At present, most methodologies proposed to control over double fed induction generators (DFIGs) are based on single machine model, where the interactions from network have been neglected. Considering this, this paper proposes a decentralized coordinated control of DFIG based on the neural interaction measurement observer. An artificial neural network is employed to approximate the nonlinear model of DFIG, and the approximation error due to neural approximation has been considered. A robust stabilization technique is also proposed to override the effect of approximation error. A 2 controller and a ∞ controller are employed to achieve specified engineering purposes, respectively. Then, the controller design is formulated as a mixed 2 / ∞ optimization with constrains of regional pole placement and proportional plus integral (PI) structure, which can be solved easily by using linear matrix inequality (LMI) technology. The results of simulations are presented and discussed, which show the capabilities of DFIG with the proposed control strategy to fault-tolerant control of the maximum power point tracking (MPPT) under slight sensor faults, low voltage ride-through (LVRT), and its contribution to power system transient stability support.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Neural Adaptive Decentralized Coordinated Control with Fault-Tolerant Capability for DFIGs under Stochastic Disturbances

Zhang

Cao

et al. 2017

Mathematical Problems in Engineering

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“…By doing so, a look-ahead simulation tool may send corrective instructions to control devices in less than half a second [4]. All these research and development efforts offer new opportunities for us to systematically design the ''immune system'' of a smart grid [21], where each individual participant continually performs self-assessments to deter, detect, respond to and restore grid components from unpredictable contingencies, and at the same time optimizing its performance in a decentralized manner [2,16].…”

Section: Introductionmentioning

confidence: 99%

Decentralized control and fair load-shedding compensations to prevent cascading failures in a smart grid

Shi

Liu

2015

International Journal of Electrical Power & Energy Systems

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a b s t r a c tEvidence shows that a small number of line contingencies in power systems may cause a large-scale blackout due to the effects of cascading failures. With the development of new technologies and the growing number of heterogeneous participants, a modern/smart grid should be able to self-heal its internal disturbances by continually performing self-assessment to deter, detect, respond to and restore from unpredictable contingencies. Along this line, this research focuses on the problem of how to prevent the occurrence of cascading failures through load shedding by considering heterogeneous shedding costs of grid participants. A fair load-shedding algorithm is proposed to solve the problem in a decentralized manner, where a load-shedding participant need only monitor its own operational status and interact with its neighboring participants. Using an embedded feedback mechanism, the fair load-shedding algorithm can determine a marginal compensation price for each load-shedding participant in real time based on the proportional fairness criterion, without knowing the shedding costs of the participants. Such fairly determined compensations can help motivate loaders/generators to actively participate in the load shedding in the face of internal disturbances. Finally, the properties of the load-shedding algorithm are evaluated by carrying out an experimental study on the standard IEEE 30 bus system. The study will offer new insights into emergency planning and design improvement of self-healing smart grids.

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“…Some decentralized approaches based on MAS have been used in [25][26][27] to improve the transient stability of power systems where the agents act in a coordinated manner. However, decentralized schemes work well when there are weak coupling in power systems which is not the case for smart grids.…”

Section: Introductionmentioning

confidence: 99%

A multi-agent approach for enhancing transient stability of smart grids

Rahman

Mahmud

Pota

et al. 2015

International Journal of Electrical Power & Energy Systems

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Decentralized coordinated control for large power system based on transient stability assessment

Cited by 28 publications

References 23 publications

Neural Adaptive Decentralized Coordinated Control with Fault-Tolerant Capability for DFIGs under Stochastic Disturbances

Neural Adaptive Decentralized Coordinated Control with Fault-Tolerant Capability for DFIGs under Stochastic Disturbances

Decentralized control and fair load-shedding compensations to prevent cascading failures in a smart grid

A multi-agent approach for enhancing transient stability of smart grids

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