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Microgrid Planner: An Open-Source Software Platform

Author

Listed:
  • Daniel Reich

    (Department of Operations Research, Naval Postgraduate School, Monterey, California 93955)

  • Leah Frye

    (Extended Campus, Naval Postgraduate School, Monterey, California 93955)

Abstract

We introduce an open-source software platform for developing microgrid planning tools. Our platform is composed of a computational layer developed in Python; a MySQL database layer; a REST API developed in Flask; a web app front end developed in Flask, HTML templates, and JavaScript; containerized deployment through Docker; and high-performance computing integration using Slurm. Our base capabilities include user accounts with authentication, user-defined distributed energy resource components and microgrids, user uploads of power load data, a core simulation method, and a microgrid sizing method. These capabilities are all integrated into a user-friendly web application, which is designed to be customized and extended. Whereas our platform already includes a useful set of microgrid planning tools, our vision is for it to bridge the active academic analytical modeling research for microgrid planning into deployable software tools that can be readily used by practitioners. In addition to describing our current capabilities, this paper details how our platform design facilitates easy adoption by other researchers developing analytical methods for microgrid planning.

Suggested Citation

  • Daniel Reich & Leah Frye, 2025. "Microgrid Planner: An Open-Source Software Platform," INFORMS Journal on Computing, INFORMS, vol. 37(3), pages 503-515, May.
  • Handle: RePEc:inm:orijoc:v:37:y:2025:i:3:p:503-515
    DOI: 10.1287/ijoc.2023.0336
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    References listed on IDEAS

    as
    1. Daniel Reich & Giovanna Oriti, 2021. "Rightsizing the Design of a Hybrid Microgrid," Energies, MDPI, vol. 14(14), pages 1-22, July.
    2. Stadler, M. & Groissböck, M. & Cardoso, G. & Marnay, C., 2014. "Optimizing Distributed Energy Resources and building retrofits with the strategic DER-CAModel," Applied Energy, Elsevier, vol. 132(C), pages 557-567.
    3. Alexander J. Zolan & Michael S. Scioletti & David P. Morton & Alexandra M. Newman, 2021. "Decomposing Loosely Coupled Mixed-Integer Programs for Optimal Microgrid Design," INFORMS Journal on Computing, INFORMS, vol. 33(4), pages 1300-1319, October.
    4. Umberto Berardi & Elisa Tomassoni & Khaled Khaled, 2020. "A Smart Hybrid Energy System Grid for Energy Efficiency in Remote Areas for the Army," Energies, MDPI, vol. 13(9), pages 1-22, May.
    Full references (including those not matched with items on IDEAS)

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