IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v154y2015icp277-289.html
   My bibliography  Save this article

Integration of decentralized energy systems in neighbourhoods using the energy hub approach

Author

Listed:
  • Orehounig, Kristina
  • Evins, Ralph
  • Dorer, Viktor

Abstract

This paper describes a method of integrating decentralized energy systems at neighbourhood scale. The method is based on the energy hub concept, which describes and manages the relation between input and output energy flows and thus can be used to optimise energy consumption. The original energy hub concept is further developed to include decentralized and local energy technologies such as photovoltaics, biomass, or small hydro power, together with district heating systems, building and district conversion and storage technologies at neighbourhood level. Additionally, input from a building simulation tool for evaluating time-dependent buildings energy demand is included in the method. The proposed approach can be used to evaluate and size urban energy systems according to their energy-autonomy, economic and ecological performance. The advantage is that the energy supply systems and local energy storage systems can be evaluated in a combined way at district scale. The suggested method allows to lower peaks in energy demands of neighbourhoods on the electrical grid and to reduce the overall consumption. The developed method is finally applied on a case study for which future energy scenarios of different implementation scale are suggested. The area is located in a village in the mountains and contains 29 buildings. Suggested scenarios include decentralized and local renewable energy sources and district and small heating networks. Results show a variation of 52–98tons of CO2 emissions, and an energy autonomy between 64% and 92%. In case of CO2 emissions, the best solution is given for a combination of multiple supply technologies and small networks which shows 46% lower emissions than for a scenario with only PV and biomass based systems.

Suggested Citation

  • Orehounig, Kristina & Evins, Ralph & Dorer, Viktor, 2015. "Integration of decentralized energy systems in neighbourhoods using the energy hub approach," Applied Energy, Elsevier, vol. 154(C), pages 277-289.
    • Handle: RePEc:eee:appene:v:154:y:2015:i:c:p:277-289
    DOI: 10.1016/j.apenergy.2015.04.114
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261915005772
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2015.04.114?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. Mancarella, Pierluigi, 2014. "MES (multi-energy systems): An overview of concepts and evaluation models," Energy, Elsevier, vol. 65(C), pages 1-17.
    2. Omu, Akomeno & Choudhary, Ruchi & Boies, Adam, 2013. "Distributed energy resource system optimisation using mixed integer linear programming," Energy Policy, Elsevier, vol. 61(C), pages 249-266.
    3. Ren, Hongbo & Gao, Weijun, 2010. "A MILP model for integrated plan and evaluation of distributed energy systems," Applied Energy, Elsevier, vol. 87(3), pages 1001-1014, March.
    4. Baetens, R. & De Coninck, R. & Van Roy, J. & Verbruggen, B. & Driesen, J. & Helsen, L. & Saelens, D., 2012. "Assessing electrical bottlenecks at feeder level for residential net zero-energy buildings by integrated system simulation," Applied Energy, Elsevier, vol. 96(C), pages 74-83.
    5. Perry, Simon & Klemeš, Jiří & Bulatov, Igor, 2008. "Integrating waste and renewable energy to reduce the carbon footprint of locally integrated energy sectors," Energy, Elsevier, vol. 33(10), pages 1489-1497.
    6. Sharafi, Masoud & ELMekkawy, Tarek Y., 2014. "Multi-objective optimal design of hybrid renewable energy systems using PSO-simulation based approach," Renewable Energy, Elsevier, vol. 68(C), pages 67-79.
    7. Petruschke, Philipp & Gasparovic, Goran & Voll, Philip & Krajačić, Goran & Duić, Neven & Bardow, André, 2014. "A hybrid approach for the efficient synthesis of renewable energy systems," Applied Energy, Elsevier, vol. 135(C), pages 625-633.
    8. Ren, Hongbo & Zhou, Weisheng & Nakagami, Ken'ichi & Gao, Weijun & Wu, Qiong, 2010. "Multi-objective optimization for the operation of distributed energy systems considering economic and environmental aspects," Applied Energy, Elsevier, vol. 87(12), pages 3642-3651, December.
    9. Weber, C. & Shah, N., 2011. "Optimisation based design of a district energy system for an eco-town in the United Kingdom," Energy, Elsevier, vol. 36(2), pages 1292-1308.
    10. Mehleri, Eugenia D. & Sarimveis, Haralambos & Markatos, Nikolaos C. & Papageorgiou, Lazaros G., 2012. "A mathematical programming approach for optimal design of distributed energy systems at the neighbourhood level," Energy, Elsevier, vol. 44(1), pages 96-104.
    11. Jennings, Mark & Fisk, David & Shah, Nilay, 2014. "Modelling and optimization of retrofitting residential energy systems at the urban scale," Energy, Elsevier, vol. 64(C), pages 220-233.
    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. Allegrini, Jonas & Orehounig, Kristina & Mavromatidis, Georgios & Ruesch, Florian & Dorer, Viktor & Evins, Ralph, 2015. "A review of modelling approaches and tools for the simulation of district-scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 1391-1404.
    2. Wouters, Carmen & Fraga, Eric S. & James, Adrian M., 2015. "An energy integrated, multi-microgrid, MILP (mixed-integer linear programming) approach for residential distributed energy system planning – A South Australian case-study," Energy, Elsevier, vol. 85(C), pages 30-44.
    3. Mavromatidis, Georgios & Orehounig, Kristina & Carmeliet, Jan, 2018. "A review of uncertainty characterisation approaches for the optimal design of distributed energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 88(C), pages 258-277.
    4. Di Somma, M. & Yan, B. & Bianco, N. & Graditi, G. & Luh, P.B. & Mongibello, L. & Naso, V., 2017. "Multi-objective design optimization of distributed energy systems through cost and exergy assessments," Applied Energy, Elsevier, vol. 204(C), pages 1299-1316.
    5. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2017. "Decarbonizing the electricity grid: The impact on urban energy systems, distribution grids and district heating potential," Applied Energy, Elsevier, vol. 191(C), pages 125-140.
    6. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimization framework for distributed energy systems with integrated electrical grid constraints," Applied Energy, Elsevier, vol. 171(C), pages 296-313.
    7. Falke, Tobias & Krengel, Stefan & Meinerzhagen, Ann-Kathrin & Schnettler, Armin, 2016. "Multi-objective optimization and simulation model for the design of distributed energy systems," Applied Energy, Elsevier, vol. 184(C), pages 1508-1516.
    8. Morvaj, Boran & Evins, Ralph & Carmeliet, Jan, 2016. "Optimising urban energy systems: Simultaneous system sizing, operation and district heating network layout," Energy, Elsevier, vol. 116(P1), pages 619-636.
    9. Najafi, Arsalan & Falaghi, Hamid & Contreras, Javier & Ramezani, Maryam, 2016. "Medium-term energy hub management subject to electricity price and wind uncertainty," Applied Energy, Elsevier, vol. 168(C), pages 418-433.
    10. Marquant, Julien F. & Evins, Ralph & Bollinger, L. Andrew & Carmeliet, Jan, 2017. "A holarchic approach for multi-scale distributed energy system optimisation," Applied Energy, Elsevier, vol. 208(C), pages 935-953.
    11. Gabrielli, Paolo & Gazzani, Matteo & Martelli, Emanuele & Mazzotti, Marco, 2018. "Optimal design of multi-energy systems with seasonal storage," Applied Energy, Elsevier, vol. 219(C), pages 408-424.
    12. Wu, Qiong & Ren, Hongbo & Gao, Weijun & Ren, Jianxing, 2016. "Multi-objective optimization of a distributed energy network integrated with heating interchange," Energy, Elsevier, vol. 109(C), pages 353-364.
    13. Ferrari, Simone & Zagarella, Federica & Caputo, Paola & D'Amico, Antonino, 2019. "Results of a literature review on methods for estimating buildings energy demand at district level," Energy, Elsevier, vol. 175(C), pages 1130-1137.
    14. Li, Longxi & Mu, Hailin & Gao, Weijun & Li, Miao, 2014. "Optimization and analysis of CCHP system based on energy loads coupling of residential and office buildings," Applied Energy, Elsevier, vol. 136(C), pages 206-216.
    15. Li, Longxi & Mu, Hailin & Li, Nan & Li, Miao, 2016. "Economic and environmental optimization for distributed energy resource systems coupled with district energy networks," Energy, Elsevier, vol. 109(C), pages 947-960.
    16. Rey, Anthony & Zmeureanu, Radu, 2018. "Multi-objective optimization framework for the selection of configuration and equipment sizing of solar thermal combisystems," Energy, Elsevier, vol. 145(C), pages 182-194.
    17. David Grosspietsch & Marissa Saenger & Bastien Girod, 2019. "Matching decentralized energy production and local consumption: A review of renewable energy systems with conversion and storage technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 8(4), July.
    18. Fichera, Alberto & Frasca, Mattia & Volpe, Rosaria, 2017. "Complex networks for the integration of distributed energy systems in urban areas," Applied Energy, Elsevier, vol. 193(C), pages 336-345.
    19. Voll, Philip & Jennings, Mark & Hennen, Maike & Shah, Nilay & Bardow, André, 2015. "The optimum is not enough: A near-optimal solution paradigm for energy systems synthesis," Energy, Elsevier, vol. 82(C), pages 446-456.
    20. Yanfeng Liu & Yaxing Wang & Xi Luo, 2020. "Design and Operation Optimization of Distributed Solar Energy System Based on Dynamic Operation Strategy," Energies, MDPI, vol. 14(1), pages 1-26, December.

    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:appene:v:154:y:2015:i:c:p:277-289. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.