Nonlinear decentralized robust governor control for hydroturbo-generator sets of multi-machine system

Sun, Yongqiang; Sun, Yuanzhong; Lu, Qiang; Shao, Yimin

doi:10.1109/wcica.2000.859913

Cited by 5 publications

(2 citation statements)

References 4 publications

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“…Hydropower stations are usually located in the remote areas, they send electricity to the load center by high-voltage and long-distance line. So the hydro-generator contact with power grid can be approximately regarded as single machine infinite bus(SMIB) power system [8].The structure and equivalent circuit diagram of hydro-generator with TCBR controlled system are shown in Fig. 1.…”

Section: The Dynamic Model Of Tcbr and Hydro-generatormentioning

confidence: 99%

Multi-Index Nonlinear Coordinated Control of TCBR and Hydro-Generator Excitation

Liang

2014

AMM

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As a new FACTS device, thyristor controlled braking resistor (TCBR) is one of the effective devices to enhance transient stability of generator. In this paper, a coordinated controller for TCBR and hydro-generator excitation system with the multi-index nonlinear coordinate control method based differential geometry theory is proposed. By means of Hartman-Grobman theorem, differential geometry multi-index nonlinear control (DGMINC) design method can reassign the closed-loop system eigenvalues of linear approximate system to the nonlinear system via appropriately selecting output function parameter matrix. Therefore, the system can get good control performance. The simulation results show that TCBR and generator excitation system controlled by this coordinate control strategy can decrease the generator acceleration area rapidly when the severe fault occurred and increase deceleration area significantly after the fault is cleared. So that, power system transient stability limitation improved significantly.

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Section: The Dynamic Model Of Tcbr and Hydro-generatormentioning

confidence: 99%

Multi-Index Nonlinear Coordinated Control of TCBR and Hydro-Generator Excitation

Liang

2014

AMM

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“…Thus, it is necessary to effectively design control action in the plant with proper model representation of the system. Among the advanced techniques reported in the last decade we include using H ¥ optimal control [1], differential nonlinear geometric structure theory [2], the connectionist approach for tuning the control parameters [3], fuzzy and neural networks [4], nonlinear decentralized robust control [5], fuzzy logic [6], and so on.…”

Section: Introductionmentioning

confidence: 99%

Small hydro power plant identification using NNARX structure

Kishor

Saini

Singh

2005

Neural Comput & Applic

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A feedforward multi-layer perceptron neural network structure is developed to model the nonlinear dynamic relationship between input and output of a hydro power plant connected as single machine infinite bus system. Two independent second-order neural network nonlinear auto-regressive with exogenous signal models are used in the study. The structure selection of each independent model is based on various validation tests. The optimal brain surgeon pruning strategy adopted for optimizing the neural network structure. The network performance is studied for fixed and change in operating point.

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Nonlinear control for hydro turbine generator unit with time-varying parameters via state feedback linearization

Fang

Wen-sang

Shen

ICARCV 2004 8th Control, Automation, Robotics and Vision Conference, 2004.

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Nonlinear decentralized robust governor control for hydroturbo-generator sets of multi-machine system

Cited by 5 publications

References 4 publications

Multi-Index Nonlinear Coordinated Control of TCBR and Hydro-Generator Excitation

Multi-Index Nonlinear Coordinated Control of TCBR and Hydro-Generator Excitation

Small hydro power plant identification using NNARX structure

Nonlinear control for hydro turbine generator unit with time-varying parameters via state feedback linearization

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