Optimal design of energy conversion units for residential buildings considering German market conditions
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DOI: 10.1016/j.energy.2017.08.024
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Cited by:
- Schütz, Thomas & Schraven, Markus Hans & Fuchs, Marcus & Remmen, Peter & Müller, Dirk, 2018. "Comparison of clustering algorithms for the selection of typical demand days for energy system synthesis," Renewable Energy, Elsevier, vol. 129(PA), pages 570-582.
- Pina, Eduardo A. & Lozano, Miguel A. & Serra, Luis M., 2021. "Assessing the influence of legal constraints on the integration of renewable energy technologies in polygeneration systems for buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
- Wakui, Tetsuya & Hashiguchi, Moe & Sawada, Kento & Yokoyama, Ryohei, 2019. "Two-stage design optimization based on artificial immune system and mixed-integer linear programming for energy supply networks," Energy, Elsevier, vol. 170(C), pages 1228-1248.
- Kotzur, Leander & Markewitz, Peter & Robinius, Martin & Stolten, Detlef, 2018. "Time series aggregation for energy system design: Modeling seasonal storage," Applied Energy, Elsevier, vol. 213(C), pages 123-135.
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Keywords
Building energy systems; German regulations; Mixed-integer linear programming; Multiple energy tariffs;All these keywords.
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