Optimization Online


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

Ignacio Aravena(aravenasolis1***at***llnl.gov)
Deepak Rajan(rajan3***at***llnl.gov)
Georgios Patsakis(gpatsakis***at***berkeley.edu)
Shmuel Oren(shmuel***at***berkeley.edu)
Jennifer Rios(LJDb***at***pge.com)

Abstract: 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.

Keywords: Power system restoration, power system resilience, integer L-shaped method, power flow approximations

Category 1: Applications -- Science and Engineering (Smart Grids )

Category 2: Combinatorial Optimization (Branch and Cut Algorithms )

Category 3: Integer Programming ((Mixed) Integer Linear Programming )

Citation: Submitted to IEEE Transactions in Power Systems

Download: [PDF]

Entry Submitted: 02/06/2019
Entry Accepted: 02/06/2019
Entry Last Modified: 02/06/2019

Modify/Update this entry

  Visitors Authors More about us Links
  Subscribe, Unsubscribe
Digest Archive
Search, Browse the Repository


Coordinator's Board
Classification Scheme
Give us feedback
Optimization Journals, Sites, Societies
Mathematical Optimization Society