Tight and Compact MILP Models for Storage Operation and Unit Commitment

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Abstract

To achieve climate goals by 2050, accurate energy system optimization (MIP) models are needed to help decision-makers make investment plans. To increase accuracy, a high resolution in the temporal and spatial dimensions is needed, as well as many details on the operational capabilities of energy generators. However, this results in large-scale models that do not scale well. Thus, researchers often seek the right trade-off between computational tractability and accuracy. Here, we present a tighter formulation for optimal storage operation and investment problems, including reserves, along with the methodology we used to obtain it, based on the work of [2]. Additionally, we present some preliminary work aiming to provide tight and compact unit commitment models with different levels of detail. These models can be included in large-scale energy system optimization models to increase model accuracy while keeping the models computationally tractable.
Original languageEnglish
Title of host publicationE-ENERGY 2025 - Proceedings of the 2025 16th ACM International Conference on Future and Sustainable Energy Systems
Place of PublicationNew York, NY
PublisherAssociation for Computing Machinery (ACM)
Pages979-980
Number of pages2
ISBN (Electronic)9798400711251
DOIs
Publication statusPublished - 2025
Event16th ACM International Conference on Future and Sustainable Energy Systems, E-ENERGY 2025 - Rotterdam, Netherlands
Duration: 17 Jun 202520 Jun 2025
https://energy.acm.org/conferences/eenergy/2025/

Conference

Conference16th ACM International Conference on Future and Sustainable Energy Systems, E-ENERGY 2025
Country/TerritoryNetherlands
CityRotterdam
Period17/06/2520/06/25
Internet address

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 7 - Affordable and Clean Energy
    SDG 7 Affordable and Clean Energy

Keywords

  • convex hull
  • energy storage systems
  • energy system optimization model (ESOM)
  • linear programming (LP)
  • mixed-integer linear programming (MIP)
  • optimal investments
  • ramping
  • reserves
  • tight formulation
  • unit commitment

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