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Title: Electric Power Distribution System Model Simplification Using Segment Substitution

Abstract

Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). Finally, in contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.

Authors:
 [1];  [1];  [2];  [2]
  1. Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
  2. Univ. of Pittsburgh, PA (United States). Dept. of Electrical and Computer Engineering
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1413454
Report Number(s):
PNNL-SA-124356
Journal ID: ISSN 0885-8950; TRN: US1800428
Grant/Contract Number:  
AC05-76RL01830
Resource Type:
Accepted Manuscript
Journal Name:
IEEE Transactions on Power Systems
Additional Journal Information:
Journal Volume: 33; Journal Issue: 3; Journal ID: ISSN 0885-8950
Publisher:
IEEE
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION; Load modeling; Computational modeling; Topology; Mathematical model; Junctions; Load flow; Voltage control; Approximation algorithms; power distribution; power system modeling; power system simulation

Citation Formats

Reiman, Andrew P., McDermott, Thomas E., Akcakaya, Murat, and Reed, Gregory F. Electric Power Distribution System Model Simplification Using Segment Substitution. United States: N. p., 2017. Web. doi:10.1109/TPWRS.2017.2753100.
Reiman, Andrew P., McDermott, Thomas E., Akcakaya, Murat, & Reed, Gregory F. Electric Power Distribution System Model Simplification Using Segment Substitution. United States. https://doi.org/10.1109/TPWRS.2017.2753100
Reiman, Andrew P., McDermott, Thomas E., Akcakaya, Murat, and Reed, Gregory F. Wed . "Electric Power Distribution System Model Simplification Using Segment Substitution". United States. https://doi.org/10.1109/TPWRS.2017.2753100. https://www.osti.gov/servlets/purl/1413454.
@article{osti_1413454,
title = {Electric Power Distribution System Model Simplification Using Segment Substitution},
author = {Reiman, Andrew P. and McDermott, Thomas E. and Akcakaya, Murat and Reed, Gregory F.},
abstractNote = {Quasi-static time-series (QSTS) simulation is used to simulate the behavior of distribution systems over long periods of time (typically hours to years). The technique involves repeatedly solving the load-flow problem for a distribution system model and is useful for distributed energy resource (DER) planning. When a QSTS simulation has a small time step and a long duration, the computational burden of the simulation can be a barrier to integration into utility workflows. One way to relieve the computational burden is to simplify the system model. The segment substitution method of simplifying distribution system models introduced in this paper offers model bus reduction of up to 98% with a simplification error as low as 0.2% (0.002 pu voltage). Finally, in contrast to existing methods of distribution system model simplification, which rely on topological inspection and linearization, the segment substitution method uses black-box segment data and an assumed simplified topology.},
doi = {10.1109/TPWRS.2017.2753100},
journal = {IEEE Transactions on Power Systems},
number = 3,
volume = 33,
place = {United States},
year = {Wed Sep 20 00:00:00 EDT 2017},
month = {Wed Sep 20 00:00:00 EDT 2017}
}

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