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Challenges in reducing the computational time of QSTS simulations for distribution system analysis.

Technical Report ·
DOI:https://doi.org/10.2172/1367462· OSTI ID:1367462
 [1];  [1];  [2];  [2];  [1];  [3]
  1. Georgia Inst. of Technology, Atlanta, GA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
  3. CME International T&D, St. Bruno, QC (Canada)

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modelling and impact analysis. Unlike conventional scenario - based studies , quasi - static time - series (QSTS) simulation s can realistically model time - dependent voltage controllers and the diversity of potential impacts that can occur at different times of year . However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1 - second resolution is often required , which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled . This computational burden is a clear l imitation to the adoption of QSTS simulation s in interconnection studies and for determining optimal control solutions for utility operations . Our ongoing research to improve the speed of QSTS simulation has revealed many unique aspects of distribution system modelling and sequential power flow analysis that make fast QSTS a very difficult problem to solve. In this report , the most relevant challenges in reducing the computational time of QSTS simulations are presented: number of power flows to solve, circuit complexity, time dependence between time steps, multiple valid power flow solutions, controllable element interactions, and extensive accurate simulation analysis.

Research Organization:
Sandia National Laboratories (SNL-NM), Albuquerque, NM (United States)
Sponsoring Organization:
USDOE National Nuclear Security Administration (NNSA)
DOE Contract Number:
AC04-94AL85000
OSTI ID:
1367462
Report Number(s):
SAND--2017-5743; 653822
Country of Publication:
United States
Language:
English

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