Commissioning experience with a modern digital excitation system

Godhwani, A.; Basler, Michael; Kim, K.; Eberly, T.W.

doi:10.1109/60.678983

Cited by 37 publications

(13 citation statements)

References 2 publications

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“…Regarding the synchronous generator, although it may be represented by a seventh order nonlinear model , , it is a common practice in AVR design for the SG to be approximated by the transient model especially derived for the control design , the first order transfer function

G_{G} ((), s) = \frac{U_{g} ((), s)}{U_{f} ((), s)} = K_{G} \frac{1}{s τ_{G} + 1}

where τ G and K G represent the equivalent SG transient time constant and static gain derived from the particular generator operating point (determined by the operating SG excitation current, stator voltage, active and reactive power ), U f SG excitation voltage, and U g stator voltage RMS value. Since τ G is commonly several orders higher than τ TB (for the 300 MW aggregate presented in this paper τ G = 7 s and τ TB = 1.1 ms) the thyristor bridge time delay may be neglected, which means that its model may be approximated by the static gain K TB .…”

Section: Power Converter and Synchronous Generator Modelsmentioning

confidence: 99%

“…Regarding the synchronous generator, although it may be represented by a seventh order nonlinear model [7], [29], it is a common practice in AVR design [5][6][7][8][9] for the SG to be approximated by the transient model especially derived for the control design [7], the first order transfer function…”

Section: Power Converter and Synchronous Generator Modelsmentioning

confidence: 99%

“…Together with the standard AVR topologies based on sequential differential compensators [2] and [4] several different structures are proposed in the technical literature, based on linear and nonlinear controlling techniques. In [5,6], comprehensive surveys of PID sequential controllers used in the AVR are presented, providing an insight into the state of the art of controller tuning and operation techniques.Namely, in [5] two different approaches to PID tuning in AVR applications are outlined: (i) a tuning technique [7] based on pole placement; and (ii) a tuning technique [8] based on pole cancellation. Furthermore, these AVR design procedures are carried out by using an open circuit SG model, since in that mode of operation the designed AVR is the least robust [5], compared with other modes of SG operation.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Robust synchronous generator excitation regulator based on stabilizing feedback action

Stojić

Milinković

Veinović

et al. 2015

Int. Trans. Electr. Energ. Syst.

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Summary A new method for synchronous generator static excitation control is proposed in this paper, based on the PI controller and stabilizing feedback action. Compared with the existing solutions, this paper introduces improvements in the system's dynamic performance, robustness, and sensitivity in relation to noise, based on simplified control system structure modification. By introducing the stator voltage stabilizing feedback action, an improved level of dynamic performance is achieved, which also introduces an increased level of robustness. Furthermore, compared with sequential PID and lead–lag compensator based controllers proposed in related standards and technical papers, the system sensitivity in relation to the measurement noise is not compromised, since the differential control action is not included in the proposed controlling structure. The controller design procedure is performed by means of a frequency domain based technique, while its performance is verified by means of simulation and experimental test runs. Copyright © 2015 John Wiley & Sons, Ltd.

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G_{G} ((), s) = \frac{U_{g} ((), s)}{U_{f} ((), s)} = K_{G} \frac{1}{s τ_{G} + 1}

Section: Power Converter and Synchronous Generator Modelsmentioning

confidence: 99%

Section: Power Converter and Synchronous Generator Modelsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Robust synchronous generator excitation regulator based on stabilizing feedback action

Stojić

Milinković

Veinović

et al. 2015

Int. Trans. Electr. Energ. Syst.

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show abstract

“…The block diagram for this system is shown in Fig. 3, and the exciter model is given by [27][28][29] …”

Section: Exciter Modelmentioning

confidence: 99%

H _∞ control of single‐machine infinite bus power systems with superconducting magnetic energy storage based on energy‐shaping and backstepping

Wan

Zhao

2013

IET Control Theory & Applications

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This article studies the H ∞ control problem for single-machine infinite bus power systems with superconducting magnetic energy storage (SMES) via simultaneous design of generator excitation control and SMES control. In the control system design, the exciter dynamics and unknown external disturbances are considered for practical implementation in power systems. A new synthesis framework is proposed to address the robust control problem of power systems with SMES. First, from the energy perspective, the interconnection and damping assignment (IDA) approach is applied to improve the transient performance of power systems. Second, by introducing the idea of virtual control in the design process, the authors obtain the solution of a partial differential equation that is a crucial point and cannot be obtained by using the traditional IDA method. Third, in order to enhance the robustness of the closedloop system, the authors study the H ∞ control design that is challenging and difficult for power systems considering the above mentioned practical considerations. In addition, the authors use a novel equivalent generator model to avoid using unmeasurable infinite bus voltage. Simulation results also show the effectiveness and advantage of the proposed controller.

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“…But there are still many uncertain parameters of the transfer function. In order to satisfy the qualification, pulse-response of the digital voltage regulator for DSEG is used to get the input and output data by AD block at the condition of open-loop [4][5]. Method of superposition fitting is adopted to identify those uncertain parameters and errors of the identification are compared to the actual values to confirm the veracity of the fitting function.…”

Section: Introductionmentioning

confidence: 99%

Model identification and experiment of doubly salient electrical generator

Wei

Zhang

2008

2008 34th Annual Conference of IEEE Industrial Electronics

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A new approach based on the superposition fitting method is proposed for the parameters design and optimization of the transfer function for a novel doubly salient electrical generator(DSEG) with nonlinear inductance. The method to get the sorts of transfer function is adopted to build the simulation model to identification the uncertain parameters of DSEG using pulse-response results. Simulation is given to improve the control method and enhance the system performance by using the transfer function. Experiment results from a laboratory prototype test-bed demonstrate the veracity of the function and step load performance is compared to the simulation results with the optimized correction parameters.

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Commissioning experience with a modern digital excitation system

Cited by 37 publications

References 2 publications

Robust synchronous generator excitation regulator based on stabilizing feedback action

Robust synchronous generator excitation regulator based on stabilizing feedback action

H _∞ control of single‐machine infinite bus power systems with superconducting magnetic energy storage based on energy‐shaping and backstepping

Model identification and experiment of doubly salient electrical generator

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Commissioning experience with a modern digital excitation system

Cited by 37 publications

References 2 publications

Robust synchronous generator excitation regulator based on stabilizing feedback action

Robust synchronous generator excitation regulator based on stabilizing feedback action

H ∞ control of single‐machine infinite bus power systems with superconducting magnetic energy storage based on energy‐shaping and backstepping

Model identification and experiment of doubly salient electrical generator

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Product

Resources

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H _∞ control of single‐machine infinite bus power systems with superconducting magnetic energy storage based on energy‐shaping and backstepping