Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models

Schneider, Kevin P.; Tuffner, Francis K.; Elizondo, Marcelo A.; Hansen, Jacob; Fuller, Jason C.; Chassin, David P.

doi:10.1109/tsg.2018.2794180

Title: Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models

Abstract

Running electromechanical simulations with a small time-step for a long period of time is computationally challenging, especially when large system models are used. Typically, simulations with a small time-step, 1 millisecond or less, are only run for a few seconds or a couple of minutes. While this trade-off has allowed for short duration simulations of large systems, it has prevented the complete analysis of power system phenomena that span minutes to hours, such as fault induced delayed voltage recovery. As power system operations become more complex with the deployment of new technologies, it will become more important to model dynamic behavior over greater time scales. This will include the ability to model system dynamics at the distribution level, including the end-use loads. This paper will present a computationally efficient method of adaptive dynamic simulations that enable transitions between time-series and dynamic modes, as necessary to capture system dynamics, while also being able to run for extended periods of time. This capability can support the direct analysis of dynamic events, co-simulation of transmission and distribution systems, and the development of reduced-order models.

Authors:

^[1];

^[2]

Pacific Northwest National Lab. (PNNL), Seattle, WA (United States)
SLAC National Accelerator Lab., Menlo Park, CA (United States)

Publication Date:: Tue Jan 23 00:00:00 EST 2018

Research Org.:: SLAC National Accelerator Lab., Menlo Park, CA (United States); Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

Sponsoring Org.:: USDOE

OSTI Identifier:: 1505427

Alternate Identifier(s):: OSTI ID: 1494986

Report Number(s):: PNNL-SA-127084
Journal ID: ISSN 1949-3053

Grant/Contract Number:: AC02-76SF00515; AC05-76RL01830

Resource Type:: Accepted Manuscript

Journal Name:: IEEE Transactions on Smart Grid

Additional Journal Information:: Journal Volume: 10; Journal Issue: 2; Journal ID: ISSN 1949-3053

Publisher:: IEEE

Country of Publication:: United States

Language:: English

Subject:: 24 POWER TRANSMISSION AND DISTRIBUTION; load modeling; power distribution; power system dynamics; power system simulation

Citation Formats


                    Schneider, Kevin P., Tuffner, Francis K., Elizondo, Marcelo A., Hansen, Jacob, Fuller, Jason C., and Chassin, David P. Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models.  United States: N. p., 2018. 
Web.  doi:10.1109/tsg.2018.2794180.

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                    Schneider, Kevin P., Tuffner, Francis K., Elizondo, Marcelo A., Hansen, Jacob, Fuller, Jason C., & Chassin, David P. Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models.  United States.  https://doi.org/10.1109/tsg.2018.2794180

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                    Schneider, Kevin P., Tuffner, Francis K., Elizondo, Marcelo A., Hansen, Jacob, Fuller, Jason C., and Chassin, David P. Tue .  
"Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models".  United States.  https://doi.org/10.1109/tsg.2018.2794180.  https://www.osti.gov/servlets/purl/1505427.

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@article{osti_1505427,

  title        = {Adaptive Dynamic Simulations for Distribution Systems using Multi-State Load Models},

  author       = {Schneider, Kevin P. and Tuffner, Francis K. and Elizondo, Marcelo A. and Hansen, Jacob and Fuller, Jason C. and Chassin, David P.},

  abstractNote = {Running electromechanical simulations with a small time-step for a long period of time is computationally challenging, especially when large system models are used. Typically, simulations with a small time-step, 1 millisecond or less, are only run for a few seconds or a couple of minutes. While this trade-off has allowed for short duration simulations of large systems, it has prevented the complete analysis of power system phenomena that span minutes to hours, such as fault induced delayed voltage recovery. As power system operations become more complex with the deployment of new technologies, it will become more important to model dynamic behavior over greater time scales. This will include the ability to model system dynamics at the distribution level, including the end-use loads. This paper will present a computationally efficient method of adaptive dynamic simulations that enable transitions between time-series and dynamic modes, as necessary to capture system dynamics, while also being able to run for extended periods of time. This capability can support the direct analysis of dynamic events, co-simulation of transmission and distribution systems, and the development of reduced-order models.},

  doi          = {10.1109/tsg.2018.2794180},

  journal      = {IEEE Transactions on Smart Grid},

  number       = 2,

  volume       = 10,

  place        = {United States},

  year         = {Tue Jan 23 00:00:00 EST 2018},

  month        = {Tue Jan 23 00:00:00 EST 2018}

}

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Fig. 1: State transition model for a single-phase induction motor, with allowed state transition paths shown as directional arrows.

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