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Stochastic optimal power flow by multi-variate Edgeworth expansions

Perninge, Magnus LU (2014) In Electric Power Systems Research 109. p.90-100
Abstract
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constraining the operation. Recently an extension of the stochastic optimal power flow formulation that included constraints for voltage stability as well as small-signal stability was proposed. This was done by approximating the voltage stability and small-signal stability constraint boundaries with second order approximations in... (More)
Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constraining the operation. Recently an extension of the stochastic optimal power flow formulation that included constraints for voltage stability as well as small-signal stability was proposed. This was done by approximating the voltage stability and small-signal stability constraint boundaries with second order approximations in parameter space. In this article an alternative solution method to this problem will be proposed. The new improved solution method, which is based on Edgeworth series expansions, is both more efficient and accurate. We also give details on convexity of the problem and discuss some computational issues. (C) 2013 Elsevier B.V. All rights reserved. (Less)
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author
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
SOPF, Saddle-node bifurcation, Switching loadability limit, Hopf, bifurcation, Stability boundary, Edgeworth expansions
in
Electric Power Systems Research
volume
109
pages
90 - 100
publisher
Elsevier
external identifiers
  • wos:000332496700010
  • scopus:84892762824
ISSN
1873-2046
DOI
10.1016/j.epsr.2013.12.011
language
English
LU publication?
yes
id
df247f8a-5a63-4697-bc4d-f2415e44982c (old id 4410915)
date added to LUP
2014-04-29 10:56:49
date last changed
2017-01-01 03:19:32
@article{df247f8a-5a63-4697-bc4d-f2415e44982c,
  abstract     = {Stochastic optimal power flow can provide the system operator with adequate strategies for controlling the power flow to maintain secure operation under stochastic parameter variations. One limitation of stochastic optimal power flow has been that only steady-state variable limits have been used as security constraints. In many systems voltage stability and small-signal stability also play an important role in constraining the operation. Recently an extension of the stochastic optimal power flow formulation that included constraints for voltage stability as well as small-signal stability was proposed. This was done by approximating the voltage stability and small-signal stability constraint boundaries with second order approximations in parameter space. In this article an alternative solution method to this problem will be proposed. The new improved solution method, which is based on Edgeworth series expansions, is both more efficient and accurate. We also give details on convexity of the problem and discuss some computational issues. (C) 2013 Elsevier B.V. All rights reserved.},
  author       = {Perninge, Magnus},
  issn         = {1873-2046},
  keyword      = {SOPF,Saddle-node bifurcation,Switching loadability limit,Hopf,bifurcation,Stability boundary,Edgeworth expansions},
  language     = {eng},
  pages        = {90--100},
  publisher    = {Elsevier},
  series       = {Electric Power Systems Research},
  title        = {Stochastic optimal power flow by multi-variate Edgeworth expansions},
  url          = {http://dx.doi.org/10.1016/j.epsr.2013.12.011},
  volume       = {109},
  year         = {2014},
}