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Title: RECONFIGURING POWER SYSTEMS TO MINIMIZE CASCADING FAILURES: MODELS AND ALGORITHMS

Abstract

the main goal of this project was to develop new scientific tools, based on optimization techniques, with the purpose of controlling and modeling cascading failures of electrical power transmission systems. We have developed a high-quality tool for simulating cascading failures. The problem of how to control a cascade was addressed, with the aim of stopping the cascade with a minimum of load lost. Yet another aspect of cascade is the investigation of which events would trigger a cascade, or more appropriately the computation of the most harmful initiating event given some constraint on the severity of the event. One common feature of the cascade models described (indeed, of several of the cascade models found in the literature) is that we study thermally-induced line tripping. We have produced a study that accounts for exogenous randomness (e.g. wind and ambient temperature) that could affect the thermal behavior of a line, with a focus on controlling the power flow of the line while maintaining safe probability of line overload. This was done by means of a rigorous analysis of a stochastic version of the heat equation. we incorporated a model of randomness in the behavior of wind power output; again modeling an OPF-likemore » problem that uses chance-constraints to maintain low probability of line overloads; this work has been continued so as to account for generator dynamics as well.« less

Authors:
Publication Date:
Research Org.:
Columbia Univ., New York, NY (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1127329
Report Number(s):
DE-SC0002676
DOE Contract Number:  
SC0002676
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
24 POWER TRANSMISSION AND DISTRIBUTION

Citation Formats

Bienstock, Daniel. RECONFIGURING POWER SYSTEMS TO MINIMIZE CASCADING FAILURES: MODELS AND ALGORITHMS. United States: N. p., 2014. Web. doi:10.2172/1127329.
Bienstock, Daniel. RECONFIGURING POWER SYSTEMS TO MINIMIZE CASCADING FAILURES: MODELS AND ALGORITHMS. United States. https://doi.org/10.2172/1127329
Bienstock, Daniel. 2014. "RECONFIGURING POWER SYSTEMS TO MINIMIZE CASCADING FAILURES: MODELS AND ALGORITHMS". United States. https://doi.org/10.2172/1127329. https://www.osti.gov/servlets/purl/1127329.
@article{osti_1127329,
title = {RECONFIGURING POWER SYSTEMS TO MINIMIZE CASCADING FAILURES: MODELS AND ALGORITHMS},
author = {Bienstock, Daniel},
abstractNote = {the main goal of this project was to develop new scientific tools, based on optimization techniques, with the purpose of controlling and modeling cascading failures of electrical power transmission systems. We have developed a high-quality tool for simulating cascading failures. The problem of how to control a cascade was addressed, with the aim of stopping the cascade with a minimum of load lost. Yet another aspect of cascade is the investigation of which events would trigger a cascade, or more appropriately the computation of the most harmful initiating event given some constraint on the severity of the event. One common feature of the cascade models described (indeed, of several of the cascade models found in the literature) is that we study thermally-induced line tripping. We have produced a study that accounts for exogenous randomness (e.g. wind and ambient temperature) that could affect the thermal behavior of a line, with a focus on controlling the power flow of the line while maintaining safe probability of line overload. This was done by means of a rigorous analysis of a stochastic version of the heat equation. we incorporated a model of randomness in the behavior of wind power output; again modeling an OPF-like problem that uses chance-constraints to maintain low probability of line overloads; this work has been continued so as to account for generator dynamics as well.},
doi = {10.2172/1127329},
url = {https://www.osti.gov/biblio/1127329}, journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Apr 11 00:00:00 EDT 2014},
month = {Fri Apr 11 00:00:00 EDT 2014}
}