Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design

Alexander J. Zolan, Michael S. Scioletti, David P. Morton, Alexandra M. Newman

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Microgrids are frequently employed in remote regions, in part because access to a larger electric grid is impossible, difficult, or compromises reliability and independence. Although small microgrids often employ spot generation, in which a diesel generator is attached directly to a load, microgrids that combine these individual loads and augment generators with photovoltaic cells and batteries as a distributed energy system are emerging as a safer, less costly alternative. We present a model that seeks the minimumcost microgrid design and ideal dispatched power to support a small remote site for one year with hourly fidelity under a detailed battery model; this mixed-integer nonlinear program (MINLP) is intractable with commercial solvers but loosely coupled with respect to time. A mixed-integer linear program (MIP) approximates the model, and a partitioning scheme linearizes the bilinear terms. We introduce a novel policy for loosely coupled MIPs in which the system reverts to equivalent conditions at regular time intervals; this separates the problem into subproblems that we solve in parallel. We obtain solutions within 5% of optimality in at most six minutes across 14 MIP instances from the literature and solutions within 5% of optimality to the MINLP instances within 20 minutes.

Original languageEnglish (US)
Pages (from-to)1300-1319
Number of pages20
JournalINFORMS Journal on Computing
Volume33
Issue number4
DOIs
StatePublished - Sep 2021

Keywords

  • decomposition
  • design and dispatch
  • microgrid
  • mixed-integer programming

ASJC Scopus subject areas

  • Software
  • Information Systems
  • Computer Science Applications
  • Management Science and Operations Research

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