IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v59y2013icp365-376.html
   My bibliography  Save this article

Optimal design and operation of building services using mixed-integer linear programming techniques

Author

Listed:
  • Ashouri, Araz
  • Fux, Samuel S.
  • Benz, Michael J.
  • Guzzella, Lino

Abstract

As mandated by several directives issued by the European Union, starting from 2020, new buildings must be designed and constructed as low-energy buildings. This situation is to be achieved mostly by an installation of renewable energy technologies, storage systems, and improved insulations. As a result, the capital cost of these building systems and thus the potential for optimization will grow significantly. In addition, on the electric supply side, a smart grid with time-varying electricity tariffs may be established. These two directions of impact offer the opportunity to optimize the interactions between the so-called smart building and the distribution grid. Due to the stringent requirements for such future building systems, their complexity of design and control will increase inevitably. Therefore, in this paper a design framework for the optimal selection and sizing of a smart building system is presented. Various building services such as thermal and electrical storages, heating and cooling systems, and renewable energy sources are modeled and implemented using mixed-integer linear programming techniques. In order to enable a reasonable comparison of various configurations, optimal operating strategies are computed in parallel. Finally, the impact of regulatory policies and variable pricing systems on the design of the building components are examined.

Suggested Citation

  • Ashouri, Araz & Fux, Samuel S. & Benz, Michael J. & Guzzella, Lino, 2013. "Optimal design and operation of building services using mixed-integer linear programming techniques," Energy, Elsevier, vol. 59(C), pages 365-376.
    • Handle: RePEc:eee:energy:v:59:y:2013:i:c:p:365-376
    DOI: 10.1016/j.energy.2013.06.053
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544213005525
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2013.06.053?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Fazlollahi, Samira & Mandel, Pierre & Becker, Gwenaelle & Maréchal, Francois, 2012. "Methods for multi-objective investment and operating optimization of complex energy systems," Energy, Elsevier, vol. 45(1), pages 12-22.
    2. Koeppel, Gaudenz & Andersson, Göran, 2009. "Reliability modeling of multi-carrier energy systems," Energy, Elsevier, vol. 34(3), pages 235-244.
    3. Hadjipaschalis, Ioannis & Poullikkas, Andreas & Efthimiou, Venizelos, 2009. "Overview of current and future energy storage technologies for electric power applications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1513-1522, August.
    4. Moreno, Blanca & López, Ana J. & García-Álvarez, María Teresa, 2012. "The electricity prices in the European Union. The role of renewable energies and regulatory electric market reforms," Energy, Elsevier, vol. 48(1), pages 307-313.
    5. Fabrizio, Enrico & Corrado, Vincenzo & Filippi, Marco, 2010. "A model to design and optimize multi-energy systems in buildings at the design concept stage," Renewable Energy, Elsevier, vol. 35(3), pages 644-655.
    6. Cardinale, N. & Piccininni, F. & Stefanizzi, P., 2003. "Economic optimization of low-flow solar domestic hot water plants," Renewable Energy, Elsevier, vol. 28(12), pages 1899-1914.
    7. Lozano, Miguel A. & Ramos, Jose C. & Serra, Luis M., 2010. "Cost optimization of the design of CHCP (combined heat, cooling and power) systems under legal constraints," Energy, Elsevier, vol. 35(2), pages 794-805.
    8. Arcuri, P. & Florio, G. & Fragiacomo, P., 2007. "A mixed integer programming model for optimal design of trigeneration in a hospital complex," Energy, Elsevier, vol. 32(8), pages 1430-1447.
    9. Ai, B. & Yang, H. & Shen, H. & Liao, X., 2003. "Computer-aided design of PV/wind hybrid system," Renewable Energy, Elsevier, vol. 28(10), pages 1491-1512.
    10. Fux, Samuel F. & Benz, Michael J. & Guzzella, Lino, 2013. "Economic and environmental aspects of the component sizing for a stand-alone building energy system: A case study," Renewable Energy, Elsevier, vol. 55(C), pages 438-447.
    11. Bornatico, Raffaele & Pfeiffer, Michael & Witzig, Andreas & Guzzella, Lino, 2012. "Optimal sizing of a solar thermal building installation using particle swarm optimization," Energy, Elsevier, vol. 41(1), pages 31-37.
    12. Dufo-López, Rodolfo & Bernal-Agustín, José L. & Contreras, Javier, 2007. "Optimization of control strategies for stand-alone renewable energy systems with hydrogen storage," Renewable Energy, Elsevier, vol. 32(7), pages 1102-1126.
    13. Hakimi, S.M. & Moghaddas-Tafreshi, S.M., 2009. "Optimal sizing of a stand-alone hybrid power system via particle swarm optimization for Kahnouj area in south-east of Iran," Renewable Energy, Elsevier, vol. 34(7), pages 1855-1862.
    14. Mavrotas, George & Diakoulaki, Danae & Florios, Kostas & Georgiou, Paraskevas, 2008. "A mathematical programming framework for energy planning in services' sector buildings under uncertainty in load demand: The case of a hospital in Athens," Energy Policy, Elsevier, vol. 36(7), pages 2415-2429, July.
    15. Nemet, Andreja & Klemeš, Jiří Jaromír & Varbanov, Petar Sabev & Kravanja, Zdravko, 2012. "Methodology for maximising the use of renewables with variable availability," Energy, Elsevier, vol. 44(1), pages 29-37.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Ashouri, Araz & Petrini, Flavio & Bornatico, Raffaele & Benz, Michael J., 2014. "Sensitivity analysis for robust design of building energy systems," Energy, Elsevier, vol. 76(C), pages 264-275.
    2. Mirko M. Stojiljković & Mladen M. Stojiljković & Bratislav D. Blagojević, 2014. "Multi-Objective Combinatorial Optimization of Trigeneration Plants Based on Metaheuristics," Energies, MDPI, vol. 7(12), pages 1-28, December.
    3. Mallikarjun, Sreekanth & Lewis, Herbert F., 2014. "Energy technology allocation for distributed energy resources: A strategic technology-policy framework," Energy, Elsevier, vol. 72(C), pages 783-799.
    4. Wakui, Tetsuya & Yokoyama, Ryohei, 2015. "Optimal structural design of residential cogeneration systems with battery based on improved solution method for mixed-integer linear programming," Energy, Elsevier, vol. 84(C), pages 106-120.
    5. Fux, Samuel F. & Benz, Michael J. & Guzzella, Lino, 2013. "Economic and environmental aspects of the component sizing for a stand-alone building energy system: A case study," Renewable Energy, Elsevier, vol. 55(C), pages 438-447.
    6. Wakui, Tetsuya & Kawayoshi, Hiroki & Yokoyama, Ryohei, 2016. "Optimal structural design of residential power and heat supply devices in consideration of operational and capital recovery constraints," Applied Energy, Elsevier, vol. 163(C), pages 118-133.
    7. Fazlollahi, Samira & Mandel, Pierre & Becker, Gwenaelle & Maréchal, Francois, 2012. "Methods for multi-objective investment and operating optimization of complex energy systems," Energy, Elsevier, vol. 45(1), pages 12-22.
    8. Carvalho, Monica & Lozano, Miguel A. & Serra, Luis M., 2012. "Multicriteria synthesis of trigeneration systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 91(1), pages 245-254.
    9. Safaei, Amir & Freire, Fausto & Antunes, Carlos Henggeler, 2013. "A model for optimal energy planning of a commercial building integrating solar and cogeneration systems," Energy, Elsevier, vol. 61(C), pages 211-223.
    10. Lythcke-Jørgensen, Christoffer Ernst & Münster, Marie & Ensinas, Adriano Viana & Haglind, Fredrik, 2016. "A method for aggregating external operating conditions in multi-generation system optimization models," Applied Energy, Elsevier, vol. 166(C), pages 59-75.
    11. Fazlollahi, Samira & Becker, Gwenaelle & Ashouri, Araz & Maréchal, François, 2015. "Multi-objective, multi-period optimization of district energy systems: IV – A case study," Energy, Elsevier, vol. 84(C), pages 365-381.
    12. Li, Bei & Roche, Robin & Paire, Damien & Miraoui, Abdellatif, 2017. "Sizing of a stand-alone microgrid considering electric power, cooling/heating, hydrogen loads and hydrogen storage degradation," Applied Energy, Elsevier, vol. 205(C), pages 1244-1259.
    13. Cheng, Yaohua & Zhang, Ning & Kirschen, Daniel S. & Huang, Wujing & Kang, Chongqing, 2020. "Planning multiple energy systems for low-carbon districts with high penetration of renewable energy: An empirical study in China," Applied Energy, Elsevier, vol. 261(C).
    14. Venter, Philip van Zyl & Terblanche, Stephanus Esias & van Eldik, Martin, 2018. "Turbine investment optimisation for energy recovery plants by utilising historic steam flow profiles," Energy, Elsevier, vol. 155(C), pages 668-677.
    15. Yong Zeng & Yanpeng Cai & Guohe Huang & Jing Dai, 2011. "A Review on Optimization Modeling of Energy Systems Planning and GHG Emission Mitigation under Uncertainty," Energies, MDPI, vol. 4(10), pages 1-33, October.
    16. Milo, Aitor & Gaztañaga, Haizea & Etxeberria-Otadui, Ion & Bacha, Seddik & Rodríguez, Pedro, 2011. "Optimal economic exploitation of hydrogen based grid-friendly zero energy buildings," Renewable Energy, Elsevier, vol. 36(1), pages 197-205.
    17. Fabrizio, Enrico & Seguro, Federico & Filippi, Marco, 2014. "Integrated HVAC and DHW production systems for Zero Energy Buildings," Renewable and Sustainable Energy Reviews, Elsevier, vol. 40(C), pages 515-541.
    18. Jha, Sunil Kr. & Bilalovic, Jasmin & Jha, Anju & Patel, Nilesh & Zhang, Han, 2017. "Renewable energy: Present research and future scope of Artificial Intelligence," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 297-317.
    19. Hoffmann, Maximilian & Priesmann, Jan & Nolting, Lars & Praktiknjo, Aaron & Kotzur, Leander & Stolten, Detlef, 2021. "Typical periods or typical time steps? A multi-model analysis to determine the optimal temporal aggregation for energy system models," Applied Energy, Elsevier, vol. 304(C).
    20. Xianzheng Zhou & Chuangxin Guo & Yifei Wang & Wanqi Li, 2017. "Optimal Expansion Co-Planning of Reconfigurable Electricity and Natural Gas Distribution Systems Incorporating Energy Hubs," Energies, MDPI, vol. 10(1), pages 1-22, January.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:energy:v:59:y:2013:i:c:p:365-376. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.