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Illustrating the Benefits of Openness: A Large-Scale Spatial Economic Dispatch Model Using the Julia Language

Author

Listed:
  • Jens Weibezahn

    (Workgroup for Infrastructure Policy (WIP), Technische Universität Berlin, H 33, Straße des 17. Juni 135, 10623 Berlin, Germany)

  • Mario Kendziorski

    (Workgroup for Infrastructure Policy (WIP), Technische Universität Berlin, H 33, Straße des 17. Juni 135, 10623 Berlin, Germany)

Abstract

In this paper we introduce a five-fold approach to open science comprised of open data, open-source software (that is, programming and modeling tools, model code, and numerical solvers), as well as open-access dissemination. The advantages of open energy models are being discussed. A fully open-source bottom-up electricity sector model with high spatial resolution using the Julia programming environment is then being developed, describing source code and a data set for Germany. This large-scale model of the electricity market includes both generation dispatch from thermal and renewable sources in the spot market as well as the physical transmission network, minimizing total system costs in a linear approach. It calculates the economic dispatch on an hourly basis for a full year, taking into account demand, infeed from renewables, storage, and exchanges with neighboring countries. Following the open approach, the model code and used data set are fully publicly accessible and we use open-source solvers like ECOS and CLP. The model is then being benchmarked regarding runtime of building and solving against a representation in GAMS as a commercial algebraic modeling language and against Gurobi, CPLEX, and Mosek as commercial solvers. With this paper we demonstrate in a proof-of-concept the power and abilities, as well as the beauty of open-source modeling systems. This openness has the potential to increase the transparency of policy advice and to empower stakeholders with fewer financial possibilities.

Suggested Citation

  • Jens Weibezahn & Mario Kendziorski, 2019. "Illustrating the Benefits of Openness: A Large-Scale Spatial Economic Dispatch Model Using the Julia Language," Energies, MDPI, vol. 12(6), pages 1-21, March.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:6:p:1153-:d:216930
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    1. Ramon Abritta & Frederico Panoeiro & Leonardo Honório & Ivo Silva Junior & André Marcato & Anapaula Guimarães, 2020. "Hydroelectric Operation Optimization and Unexpected Spillage Indications," Energies, MDPI, vol. 13(20), pages 1-20, October.
    2. Xiong, Bobby & Predel, Johannes & Crespo del Granado, Pedro & Egging-Bratseth, Ruud, 2021. "Spatial flexibility in redispatch: Supporting low carbon energy systems with Power-to-Gas," Applied Energy, Elsevier, vol. 283(C).
    3. Leonard Goke & Jens Weibezahn & Christian von Hirschhausen, 2021. "A collective blueprint, not a crystal ball: How expectations and participation shape long-term energy scenarios," Papers 2112.04821, arXiv.org, revised Dec 2022.
    4. Pearson, Simon & Wellnitz, Sonja & Crespo del Granado, Pedro & Hashemipour, Naser, 2022. "The value of TSO-DSO coordination in re-dispatch with flexible decentralized energy sources: Insights for Germany in 2030," Applied Energy, Elsevier, vol. 326(C).
    5. Gi-Ho Lee & Jae-Young Park & Seung-Jun Ham & Young-Jin Kim, 2020. "Comparative Study on Optimization Solvers for Implementation of a Two-Stage Economic Dispatch Strategy in a Microgrid Energy Management System," Energies, MDPI, vol. 13(5), pages 1-21, March.
    6. Moser, A. & Muschick, D. & Gölles, M. & Nageler, P. & Schranzhofer, H. & Mach, T. & Ribas Tugores, C. & Leusbrock, I. & Stark, S. & Lackner, F. & Hofer, A., 2020. "A MILP-based modular energy management system for urban multi-energy systems: Performance and sensitivity analysis," Applied Energy, Elsevier, vol. 261(C).
    7. Yixin Huang & Xinyi Liu & Zhi Zhang & Li Yang & Zhenzhi Lin & Yangqing Dan & Ke Sun & Zhou Lan & Keping Zhu, 2020. "Multi-Stage Transmission Network Planning Considering Transmission Congestion in the Power Market," Energies, MDPI, vol. 13(18), pages 1-22, September.

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