Optimal planning of integrated multi-energy systems

I. van Beuzekom, M. Gibescu, Pierre Pinson

    Research output: Chapter in Book/Report/Conference proceedingArticle in proceedingsResearchpeer-review


    In this paper, a mathematical approach for the optimal planning of integrated energy systems is proposed. In order to address the challenges of future, RES-dominated energy systems, the model deliberates between the expansion of traditional energy infrastructures, the integration of these infrastructures using conversion technologies (e.g. gas-to-electricity-and-heat, power-to-heat, power-to-gas), and the placement of energy storage. The model is demonstrated using a representative case study from the city of Eindhoven. Current energy data from 2015 is combined with city development scenarios and sustainability goals for 2030 and 2045. Optimal green- and brownfield designs for a district's future integrated energy system are compared using a one-step, as well as a two-step planning approach. As expected, the greenfield designs are more cost efficient, as their results are not constrained by the existing infrastructure.
    Original languageEnglish
    Title of host publicationProceedings of 2017 Ieee Manchester Powertech
    Number of pages6
    Publication date2017
    Pages6 pp.
    ISBN (Print)9781509042371
    Publication statusPublished - 2017
    Event12th IEEE Power and Energy Society PowerTech Conference: Towards and Beyond Sustainable Energy Systems - University Place, University of Manchester., Manchester, United Kingdom
    Duration: 18 Jun 201722 Jun 2017


    Conference12th IEEE Power and Energy Society PowerTech Conference
    LocationUniversity Place, University of Manchester.
    Country/TerritoryUnited Kingdom


    • Energy and environmental policy, economics and legislation
    • Energy resources and fuels
    • Energy resources
    • Planning
    • Environmental factors
    • Optimisation techniques
    • RES dominated energy systems
    • Investment
    • Resistance heating
    • Cogeneration
    • Mathematical model
    • Urban areas
    • Energy storage


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