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

Abstract

The deployment of new sensors and devices on electric distribution systems is increasing the awareness of phenomena characterized by intermittent periods of highly dynamic activity that occur within extended periods of relatively static behavior. The deployment of new devices has enabled the observation of these phenomena; however, the currently available simulation methods cannot accurately reproduce the entire system behavior. Existing simulation methods, and their associated models, are able to capture portions of these phenomena, but there is not a method for efficiently modeling the entire event in a single simulation. This paper presents a novel method of adaptive simulation that enables automated transitions between quasi-static time-series and electromechancial simulation modes, as necessary to capture relevant system dynamics. The transitions between the simulation modes are triggered automatically during the running simulation based on the evolution of the system variables, utilizing multistate modes for generators and motors. This method allows for a single simulation that spans the entire time-frame, has the ability to capture dynamic events, and includes all relevant power system controls. In conclusion, the method of adaptive simulation can support the direct analysis of dynamic power system events, co-simulation of transmission and distribution systems, the development of control systems, andmore » the development of reduced-order models.« less

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [2]
  1. Pacific Northwest National Lab. (PNNL), Seattle, WA (United States)
  2. SLAC National Accelerator Lab., Menlo Park, CA (United States)
Publication Date:
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.
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. doi:10.1109/tsg.2018.2794180.
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. doi:10.1109/tsg.2018.2794180. https://www.osti.gov/servlets/purl/1505427.
@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 = {The deployment of new sensors and devices on electric distribution systems is increasing the awareness of phenomena characterized by intermittent periods of highly dynamic activity that occur within extended periods of relatively static behavior. The deployment of new devices has enabled the observation of these phenomena; however, the currently available simulation methods cannot accurately reproduce the entire system behavior. Existing simulation methods, and their associated models, are able to capture portions of these phenomena, but there is not a method for efficiently modeling the entire event in a single simulation. This paper presents a novel method of adaptive simulation that enables automated transitions between quasi-static time-series and electromechancial simulation modes, as necessary to capture relevant system dynamics. The transitions between the simulation modes are triggered automatically during the running simulation based on the evolution of the system variables, utilizing multistate modes for generators and motors. This method allows for a single simulation that spans the entire time-frame, has the ability to capture dynamic events, and includes all relevant power system controls. In conclusion, the method of adaptive simulation can support the direct analysis of dynamic power system events, co-simulation of transmission and distribution systems, the development of control 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 = {2018},
month = {1}
}

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Figures / Tables:

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

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