A scalable mixed-integer decomposition approach for optimal power system restoration

Journal Article · Thu Jan 17 04:00:00 EST 2019 · Proposed Journal Article, unpublished

OSTI ID:1642361

Aravena, I ^[1]; Rajan, D ^[1]; Patsakis, G ^[2]; Oren, S ^[2]; Rios, J ^[3]

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1. Lawrence Livermore National Laboratory
2. UC Berkeley
3. PG&E

The optimal restoration problem lies at the foundation of the evaluation and improvement of resilience in power systems. In this paper we present a scalable decomposition algorithm, based on the integer L-shaped method, for solving this problem for realistic power systems. The algorithm works by partitioning the problem into a master problem and a slave problem. The master problem optimizes over energization sequences of generators, buses and branches, for the entire restoration horizon, while respecting stylized energization requirements. The slave problem verifies that there exist power flow solutions supporting the energization sequences proposed by the master problem, adding cuts to the master if an infeasible sequence is detected. The power flow verification is carried out using a piece-wise linear approximation of the power flow equations, capable of capturing overvoltage situations common in restoration procedures. We develop specialized binary cuts and hybrid Benders-binary cuts for separating infeasible islands, which are stronger than regular no-good cuts, as well as heuristics for obtaining feasible solutions. We present numerical results for the IEEE 39- and 118-bus systems, and for the Chilean 1500-bus grid, where our algorithm finds near-optimal restoration sequences orders of magnitude faster than the state-of-the-art, demonstrating the effectiveness of the proposed approach.

• Research Organization: Lawrence Livermore National Laboratory (LLNL), Livermore, CA (United States)
• Sponsoring Organization: USDOE National Nuclear Security Administration (NNSA)
• DOE Contract Number: AC52-07NA27344
• OSTI ID: 1642361
• Report Number(s): LLNL-JRNL-766247; 956525
• Journal Information: Proposed Journal Article, unpublished, Journal Name: Proposed Journal Article, unpublished Vol. 2019; ISSN 9999-9999
• Publisher: See Research Organization
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION
42 ENGINEERING
97 MATHEMATICS AND COMPUTING