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Chance-constrained AC optimal power flow: A polynomial chaos approach
Publikationstyp
Journal Article
Date Issued
2019-11
Sprache
English
Author(s)
Volume
34
Issue
6
Start Page
4806
End Page
4816
Article Number
8719988
Citation
IEEE Transactions on Power Systems 34 (6): 8719988 (2019-11)
Publisher DOI
Scopus ID
Publisher
IEEE
As the share of renewables in the grid increases, the operation of power systems becomes more challenging. The present paper proposes a method to formulate and solve chance-constrained optimal power flow while explicitly considering the full nonlinear ac power flow equations and stochastic uncertainties. We use polynomial chaos expansion to model the effects of arbitrary uncertainties of finite variance, which enables to predict and optimize the system state for a range of operating conditions. We apply chance constraints to limit the probability of violations of inequality constraints. Our method incorporates a more detailed and a more flexible description of both the controllable variables and the resulting system state than previous methods. Two case studies highlight the efficacy of the method, with a focus on satisfaction of the ac power flow equations and on the accurate computation of moments of all random variables.
Subjects
AC optimal power flow
chance constraints
polynomial chaos expansion
uncertainty
DDC Class
530: Physics