Nonlinear deterministic modeling of highly varying loads

E. O'Neill-Carrillo; G. T. Heydt; Eric Kostelich; S. S. Venkata; A. Sundaram

doi:10.1109/61.754100

Nonlinear deterministic modeling of highly varying loads

E. O'Neill-Carrillo, G. T. Heydt, Eric Kostelich, S. S. Venkata, A. Sundaram

Research output: Contribution to journal › Article › peer-review

73 Scopus citations

Abstract

Typically, the modeling of highly varying, nonlinear loads such as electric arc furnaces has involved stochastic techniques. This paper presents the use of chaotic dynamics to describe the operation of nonlinear loads. Included is a discussion of the Lyapunov exponents, a measure of chaotic behavior. The alternate approach is applied to electric arc furnaces. A tuning mode is described to develop the parameters of a chaotic model. This model is trained to have time and frequency responses that are tuned to match the current from the arc furnace under study. The simulated data are compared to actual arc furnace data to validate the model. This model is used to assess the impact of various highly varying nonlinear loads that exhibit chaos in power systems.

Original language	English (US)
Pages (from-to)	537-542
Number of pages	6
Journal	IEEE Transactions on Power Delivery
Volume	14
Issue number	2
DOIs	https://doi.org/10.1109/61.754100
State	Published - Apr 1999

ASJC Scopus subject areas

Energy Engineering and Power Technology
Electrical and Electronic Engineering

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10.1109/61.754100

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title = "Nonlinear deterministic modeling of highly varying loads",

abstract = "Typically, the modeling of highly varying, nonlinear loads such as electric arc furnaces has involved stochastic techniques. This paper presents the use of chaotic dynamics to describe the operation of nonlinear loads. Included is a discussion of the Lyapunov exponents, a measure of chaotic behavior. The alternate approach is applied to electric arc furnaces. A tuning mode is described to develop the parameters of a chaotic model. This model is trained to have time and frequency responses that are tuned to match the current from the arc furnace under study. The simulated data are compared to actual arc furnace data to validate the model. This model is used to assess the impact of various highly varying nonlinear loads that exhibit chaos in power systems.",

author = "E. O'Neill-Carrillo and Heydt, {G. T.} and Eric Kostelich and Venkata, {S. S.} and A. Sundaram",

note = "Funding Information: The authors wish to acknowledge the support from the Electric Power Research Institute and the National Science Foundation Industry-University Cooperative Research Center for the Advanced Control of Energy and Power Systems. Eric Kostelich was supported in part by the Department of Energy Office of Scientific Computing and by the NSF Division of Mathematical Sciences. The authors thank Mr. Tom Key of the EPFU Power Electronics Applications Center in Knoxville, TN for supplying very useful data. Dr. Baj Agrawal is also thanked for his help in this work.",

year = "1999",

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doi = "10.1109/61.754100",

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pages = "537--542",

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publisher = "Institute of Electrical and Electronics Engineers Inc.",

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AU - O'Neill-Carrillo, E.

AU - Heydt, G. T.

AU - Kostelich, Eric

AU - Venkata, S. S.

AU - Sundaram, A.

N1 - Funding Information: The authors wish to acknowledge the support from the Electric Power Research Institute and the National Science Foundation Industry-University Cooperative Research Center for the Advanced Control of Energy and Power Systems. Eric Kostelich was supported in part by the Department of Energy Office of Scientific Computing and by the NSF Division of Mathematical Sciences. The authors thank Mr. Tom Key of the EPFU Power Electronics Applications Center in Knoxville, TN for supplying very useful data. Dr. Baj Agrawal is also thanked for his help in this work.

PY - 1999/4

Y1 - 1999/4

N2 - Typically, the modeling of highly varying, nonlinear loads such as electric arc furnaces has involved stochastic techniques. This paper presents the use of chaotic dynamics to describe the operation of nonlinear loads. Included is a discussion of the Lyapunov exponents, a measure of chaotic behavior. The alternate approach is applied to electric arc furnaces. A tuning mode is described to develop the parameters of a chaotic model. This model is trained to have time and frequency responses that are tuned to match the current from the arc furnace under study. The simulated data are compared to actual arc furnace data to validate the model. This model is used to assess the impact of various highly varying nonlinear loads that exhibit chaos in power systems.

AB - Typically, the modeling of highly varying, nonlinear loads such as electric arc furnaces has involved stochastic techniques. This paper presents the use of chaotic dynamics to describe the operation of nonlinear loads. Included is a discussion of the Lyapunov exponents, a measure of chaotic behavior. The alternate approach is applied to electric arc furnaces. A tuning mode is described to develop the parameters of a chaotic model. This model is trained to have time and frequency responses that are tuned to match the current from the arc furnace under study. The simulated data are compared to actual arc furnace data to validate the model. This model is used to assess the impact of various highly varying nonlinear loads that exhibit chaos in power systems.

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Nonlinear deterministic modeling of highly varying loads

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