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The Optimal Power Flow Operator: Theory and Computation

Zhou, Fengyu and Anderson, James and Low, Steven H. (2020) The Optimal Power Flow Operator: Theory and Computation. IEEE Transactions on Control of Network Systems . ISSN 2325-5870. (In Press)

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Optimal power flow (OPF) problems are mathematical programs to determine how to distribute power over networks subject to power flow and operational constraints. In this paper, we treat an OPF problem as an operator that maps user demand to generated power, and allow the problem parameters to take values in some admissible set. We formalize this operator theoretic approach, define and characterize restricted parameter sets under which the mapping has a singleton output, independent binding constraints, and is differentiable. We show that for any power network, these analytical properties hold under almost all operating conditions and can thus be relied upon in applications. We further provide a closed-form expression for the Jacobian matrix of the OPF operator and describe how various derivatives can be computed using a recently proposed scheme based on homogenous self-dual embedding. In contrast to related work in the optimization literature, our results have a clear interpretation with respect to the power network under study.

Item Type:Article
Related URLs:
URLURL TypeDescription Paper
Zhou, Fengyu0000-0002-2639-6491
Anderson, James0000-0002-2832-8396
Low, Steven H.0000-0001-6476-3048
Additional Information:© 2020 IEEE. This work was funded by NSF grants CCF 1637598, CPS 1739355, and ECCS 1619352, PNNL grant 424858, and through the ARPA-E GRID DATA program.
Funding AgencyGrant Number
Battelle Memorial Institute424858
Advanced Research Projects Agency-Energy (ARPA-E)DE-AR0000699
Subject Keywords:Analysis, optimal power flow, linear programming
Record Number:CaltechAUTHORS:20200707-114446351
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Usage Policy:No commercial reproduction, distribution, display or performance rights in this work are provided.
ID Code:104253
Deposited By: Tony Diaz
Deposited On:07 Jul 2020 19:11
Last Modified:06 Jan 2021 18:48

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