Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design
| Autor: | Michael Scioletti, David P. Morton, Alex Zolan, Alexandra M. Newman |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
Mathematical optimization
021103 operations research Computer science 0211 other engineering and technologies General Engineering 02 engineering and technology Grid Decomposition (computer science) Independence (mathematical logic) 021108 energy Microgrid Integer programming Reliability (statistics) Integer (computer science) |
| Zdroj: | INFORMS Journal on Computing. |
| ISSN: | 1526-5528 1091-9856 |
| Popis: | 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 minimum-cost 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|