A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems

Petra, Cosmin G.; Aravena, Ignacio

doi:10.1287/opre.2022.0229

A Surrogate-Based Asynchronous Decomposition Technique for Realistic Security-Constrained Optimal Power Flow Problems

Journal Article · Fri Jul 14 00:00:00 EDT 2023 · Operations Research

DOI:https://doi.org/10.1287/opre.2022.0229· OSTI ID:2282412

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Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Here we present a decomposition approach for obtaining good feasible solutions for the security-constrained, alternating-current, optimal power flow (SC-AC-OPF) problem at an industrial scale and under real-world time and computational limits. The approach was designed while preparing and participating in ARPA-E’s Grid Optimization Competition (GOC) Challenge 1. The challenge focused on a near-real-time version of the SC-AC-OPF problem, where a base operating point is optimized, taking into account possible single-element contingencies, after which the system adapts its operating point following the response of automatic frequency droop controllers and voltage regulators. Our solution approach for this problem relies on state-of-the-art nonlinear programming algorithms, and it employs nonconvex relaxations for complementarity constraints, a specialized two-stage decomposition technique with sparse approximations of recourse terms and contingency ranking and prescreening. The paper describes and justifies our approach and outlines the features of its implementation, including functions and derivatives evaluation, warm-starting strategies, and asynchronous parallelism. We discuss the results of the independent benchmark of our approach by ARPA-E’s GOC team in Challenge 1, where it was found to consistently produce high-quality solutions across a wide range of network sizes and difficulty, and conclude by outlining future extensions of the approach.

View Accepted Manuscript (DOE)

Research Organization:: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA); USDOE Office of Science (SC)

Grant/Contract Number:: AC52-07NA27344

OSTI ID:: 2282412

Report Number(s):: LLNL--JRNL-820136; 1031331

Journal Information:: Operations Research, Journal Name: Operations Research Journal Issue: 6 Vol. 71; ISSN 0030-364X

Publisher:: INFORMSCopyright Statement

Country of Publication:: United States

Language:: English

References (15)

On the implementation of an interior-point filter line-search algorithm for large-scale nonlinear programming Wächter, Andreas; Biegler, Lorenz T. Mathematical Programming, Vol. 106, Issue 1 https://doi.org/10.1007/s10107-004-0559-y	journal	April 2005
Critical review of recent advances and further developments needed in AC optimal power flow Capitanescu, Florin Electric Power Systems Research, Vol. 136 https://doi.org/10.1016/j.epsr.2016.02.008	journal	July 2016
The SC1 property of the squared norm of the SOC Fischer–Burmeister function Chen, Jein-Shan; Sun, Defeng; Sun, Jie Operations Research Letters, Vol. 36, Issue 3 https://doi.org/10.1016/j.orl.2007.08.005	journal	May 2008
Strong NP-hardness of AC power flows feasibility Bienstock, Daniel; Verma, Abhinav Operations Research Letters, Vol. 47, Issue 6 https://doi.org/10.1016/j.orl.2019.08.009	journal	November 2019
Convex Optimization Boyd, Stephen; Vandenberghe, Lieven https://doi.org/10.1017/CBO9780511804441	book	January 2004
Optimizing Primary Response in Preventive Security-Constrained Optimal Power Flow Dvorkin, Yury; Henneaux, Pierre; Kirschen, Daniel S. IEEE Systems Journal, Vol. 12, Issue 1 https://doi.org/10.1109/JSYST.2016.2527726	journal	March 2018
Contingency Filtering Techniques for Preventive Security-Constrained Optimal Power Flow Capitanescu, Florin; Glavic, Mevludin; Ernst, Damien IEEE Transactions on Power Systems, Vol. 22, Issue 4 https://doi.org/10.1109/TPWRS.2007.907528	journal	November 2007
Contingency Ranking With Respect to Overloads in Very Large Power Systems Taking Into Account Uncertainty, Preventive, and Corrective Actions Fliscounakis, Stephane; Panciatici, Patrick; Capitanescu, Florin IEEE Transactions on Power Systems, Vol. 28, Issue 4 https://doi.org/10.1109/TPWRS.2013.2251015	journal	November 2013
Local Solutions of the Optimal Power Flow Problem Bukhsh, Waqquas A.; Grothey, Andreas; McKinnon, Ken I. M. IEEE Transactions on Power Systems, Vol. 28, Issue 4 https://doi.org/10.1109/TPWRS.2013.2274577	journal	November 2013
A Generic Approach for Solving Nonlinear-Discrete Security-Constrained Optimal Power Flow Problems in Large-Scale Systems Platbrood, Ludovic; Capitanescu, Florin; Merckx, Christian IEEE Transactions on Power Systems, Vol. 29, Issue 3 https://doi.org/10.1109/TPWRS.2013.2289990	journal	May 2014
AC-Feasibility on Tree Networks is NP-Hard Lehmann, Karsten; Grastien, Alban; Van Hentenryck, Pascal IEEE Transactions on Power Systems, Vol. 31, Issue 1 https://doi.org/10.1109/TPWRS.2015.2407363	journal	January 2016
Tutorial on Stochastic Optimization in Energy—Part I: Modeling and Policies Powell, Warren B.; Meisel, Stephan IEEE Transactions on Power Systems, Vol. 31, Issue 2 https://doi.org/10.1109/TPWRS.2015.2424974	journal	March 2016
New Formulation and Strong MISOCP Relaxations for AC Optimal Transmission Switching Problem Kocuk, Burak; Dey, Santanu S.; Sun, Xu Andy IEEE Transactions on Power Systems, Vol. 32, Issue 6 https://doi.org/10.1109/TPWRS.2017.2666718	journal	November 2017
Verification of Neural Network Behaviour: Formal Guarantees for Power System Applications Venzke, Andreas; Chatzivasileiadis, Spyros IEEE Transactions on Smart Grid, Vol. 12, Issue 1 https://doi.org/10.1109/TSG.2020.3009401	journal	January 2021
An Augmented Incomplete Factorization Approach for Computing the Schur Complement in Stochastic Optimization Petra, Cosmin G.; Schenk, Olaf; Lubin, Miles SIAM Journal on Scientific Computing, Vol. 36, Issue 2 https://doi.org/10.1137/130908737	journal	January 2014