Decentralized control of oscillatory dynamics in power systems using an extended LQR

Shrivastava, Abhinav; Pal, Bikash C.

doi:10.1109/pesgm.2016.7741163

Cited by 22 publications

(42 citation statements)

References 10 publications

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“…The 68-bus system is a widely studied system [2], and several solutions for robust damping of all the electromechanical modes in the system are available ( [16] and [17] are examples). Out of these solutions, only [17] relies solely on PSSs for providing robust damping.…”

Section: F Benchmark 6: 68-bus Systemmentioning

confidence: 99%

Benchmark Models for the Analysis and Control of Small-Signal Oscillatory Dynamics in Power Systems

Cañizares

Fernandes

Geraldi

et al. 2017

IEEE Trans. Power Syst.

254

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Abstract-This paper summarizes a set of six benchmark systems for the analysis and control of electromechanical oscillations in power systems recommended by the IEEE Task Force on Benchmark Systems for Stability Controls of the Power System Dynamic Performance Committee. The benchmark systems were chosen for their tutorial value and particular characteristics leading to control system design problems relevant to the research community. For each benchmark, the modelling guidelines are provided, along with eigenvalues and time-domain results produced with at least two simulation software, and one possible control approach is provided for each system as well. Researchers and practicing engineers are encouraged to use these benchmark systems when assessing new oscillation damping control strategies.Index terms-benchmark system, small-signal stability, electromechanical oscillations, damping controller, power system stabilizer.

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Section: F Benchmark 6: 68-bus Systemmentioning

confidence: 99%

Benchmark Models for the Analysis and Control of Small-Signal Oscillatory Dynamics in Power Systems

Cañizares

Fernandes

Geraldi

et al. 2017

IEEE Trans. Power Syst.

254

View full text Add to dashboard Cite

show abstract

“…Three different control methods have been considered to control the oscillations: (1) using PSS control, (2) using decentralized linear control, and (3) using the proposed non-linear control. The employed decentralized linear control is based on an extended linear quadratic regulator (ELQR), and has been described in [36]- [37]. A description of the PSS control method and its parameters is also available in [37].…”

Section: Case Studymentioning

confidence: 99%

“…The employed decentralized linear control is based on an extended linear quadratic regulator (ELQR), and has been described in [36]- [37]. A description of the PSS control method and its parameters is also available in [37].…”

Section: Case Studymentioning

confidence: 99%

Decentralized Nonlinear Control for Power Systems using Normal Forms and Detailed Models

Singh

Pal

2018

2018 IEEE Power &Amp; Energy Society General Meeting (PESGM)

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This paper proposes a decentralized method for nonlinear control of oscillatory dynamics in power systems. The method is applicable for ensuring both transient stability as well as small-signal stability. The method uses an optimal control law which has been derived in the general framework of nonlinear control using normal forms. The model used to derive the control law is the detailed subtransient model of synchronous machines as recommended by IEEE. Minimal approximations have been made in either the derivation or the application of the control law. The developed method also requires the application of dynamic state estimation technique. As the employed control and estimation schemes only need local measurements, the method remains completely decentralized. The method has been demonstrated as an effective tool to prevent blackouts by simulating a major disturbance in a benchmark power system model and its subsequent control using the proposed method.

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“…Three different control methods have been considered 648 to control the oscillations: (1) using PSS control, (2) using de-649 centralized linear control, and (3) using the proposed non-linear 650 control. The employed decentralized linear control is based on 651 an extended linear quadratic regulator (ELQR), and has been de-652 scribed in [36]- [37]. A description of the PSS control method 653 and its parameters is also available in [37].…”

Section: Case Studymentioning

confidence: 99%

Decentralized Nonlinear Control for Power Systems Using Normal Forms and Detailed Models

Singh

Pal

2018

IEEE Trans. Power Syst.

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This paper proposes a decentralized method for non-4 linear control of oscillatory dynamics in power systems. The 5 method is applicable for ensuring both transient stability and 6 small-signal stability. The method uses an optimal control law, 7 which has been derived in the general framework of nonlinear 8 control using normal forms. The model used to derive the control 9 law is the detailed subtransient model of synchronous machines, 10 as recommended by the IEEE. Minimal approximations have been 11 made in either the derivation or the application of the control law. 12 The developed method also requires the application of the dynamic 13 state estimation technique. As the employed control and estimation 14 schemes only need local measurements, the method remains com-15 pletely decentralized. The method has been demonstrated as an 16 effective tool to prevent blackouts by simulating a major distur-17 bance in a benchmark power system model and its subsequent 18 control using the proposed method.

show abstract

Decentralized control of oscillatory dynamics in power systems using an extended LQR

Cited by 22 publications

References 10 publications

Benchmark Models for the Analysis and Control of Small-Signal Oscillatory Dynamics in Power Systems

Benchmark Models for the Analysis and Control of Small-Signal Oscillatory Dynamics in Power Systems

Decentralized Nonlinear Control for Power Systems using Normal Forms and Detailed Models

Decentralized Nonlinear Control for Power Systems Using Normal Forms and Detailed Models

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