IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v206y2017icp22-31.html
   My bibliography  Save this article

An assessment framework to quantify the interaction between the built environment and the electricity grid

Author

Listed:
  • Cubi, Eduard
  • Akbilgic, Oguz
  • Bergerson, Joule

Abstract

Electricity consumption in buildings is highly variable on time scales of seasons, hours, minutes, and even seconds. Yet, energy performance in building sustainability standards and rating systems is typically assessed in terms of total annual energy use, cost, and/or GHG emissions. Given that in North America buildings account for between 45 and 75% (depending on the region) of total electricity consumed, it is relevant to define an assessment framework to quantify the impact of variability in building electricity demand on the electricity system. This study proposes “Grid Compensation Scores” (GCS) that assess the contribution of a building electricity demand profile to increasing or decreasing the variability in the system electricity demand profile.

Suggested Citation

  • Cubi, Eduard & Akbilgic, Oguz & Bergerson, Joule, 2017. "An assessment framework to quantify the interaction between the built environment and the electricity grid," Applied Energy, Elsevier, vol. 206(C), pages 22-31.
    • Handle: RePEc:eee:appene:v:206:y:2017:i:c:p:22-31
    DOI: 10.1016/j.apenergy.2017.08.150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261917311650
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2017.08.150?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. Stinner, Sebastian & Huchtemann, Kristian & Müller, Dirk, 2016. "Quantifying the operational flexibility of building energy systems with thermal energy storages," Applied Energy, Elsevier, vol. 181(C), pages 140-154.
    2. Cubi, Eduard & Doluweera, Ganesh & Bergerson, Joule, 2015. "Incorporation of electricity GHG emissions intensity variability into building environmental assessment," Applied Energy, Elsevier, vol. 159(C), pages 62-69.
    3. Agrell, Per J. & Bogetoft, Peter & Mikkers, Misja, 2013. "Smart-grid investments, regulation and organization," Energy Policy, Elsevier, vol. 52(C), pages 656-666.
    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. Schill, Wolf-Peter, 2014. "Residual Load, Renewable Surplus Generation and Storage Requirements in Germany," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 73, pages 65-79.
    6. Stoppato, A., 2008. "Life cycle assessment of photovoltaic electricity generation," Energy, Elsevier, vol. 33(2), pages 224-232.
    7. Nicolosi, Marco, 2010. "Wind power integration and power system flexibility-An empirical analysis of extreme events in Germany under the new negative price regime," Energy Policy, Elsevier, vol. 38(11), pages 7257-7268, November.
    8. Ottesen, Stig Odegaard & Tomasgard, Asgeir, 2015. "A stochastic model for scheduling energy flexibility in buildings," Energy, Elsevier, vol. 88(C), pages 364-376.
    9. Salom, Jaume & Marszal, Anna Joanna & Widén, Joakim & Candanedo, José & Lindberg, Karen Byskov, 2014. "Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data," Applied Energy, Elsevier, vol. 136(C), pages 119-131.
    10. Klein, Konstantin & Herkel, Sebastian & Henning, Hans-Martin & Felsmann, Clemens, 2017. "Load shifting using the heating and cooling system of an office building: Quantitative potential evaluation for different flexibility and storage options," Applied Energy, Elsevier, vol. 203(C), pages 917-937.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Sun, Yongjun & Huang, Gongsheng & Xu, Xinhua & Lai, Alvin Chi-Keung, 2018. "Building-group-level performance evaluations of net zero energy buildings with non-collaborative controls," Applied Energy, Elsevier, vol. 212(C), pages 565-576.
    2. Michel Noussan & Roberta Roberto & Benedetto Nastasi, 2018. "Performance Indicators of Electricity Generation at Country Level—The Case of Italy," Energies, MDPI, vol. 11(3), pages 1-14, March.
    3. Gao, Dian-ce & Sun, Yongjun & Zhou, Chuanwen & Bu, Yu & Bao, Yan & Chai, Jiale, 2020. "Numerical and experimental study on a double-layered coating design using supplemental property particles for achieving user-desired thermal and aesthetic performance," Energy, Elsevier, vol. 211(C).

    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. Awan, Muhammad Bilal & Sun, Yongjun & Lin, Wenye & Ma, Zhenjun, 2023. "A framework to formulate and aggregate performance indicators to quantify building energy flexibility," Applied Energy, Elsevier, vol. 349(C).
    2. Perera, A.T.D. & Nik, Vahid M. & Wickramasinghe, P.U. & Scartezzini, Jean-Louis, 2019. "Redefining energy system flexibility for distributed energy system design," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    3. Stinner, Sebastian & Schlösser, Tim & Huchtemann, Kristian & Müller, Dirk & Monti, Antonello, 2017. "Primary energy evaluation of heat pumps considering dynamic boundary conditions in the energy system," Energy, Elsevier, vol. 138(C), pages 60-78.
    4. Ma, Huan & Sun, Qinghan & Chen, Qun & Zhao, Tian & He, Kelun, 2023. "Exergy-based flexibility cost indicator and spatio-temporal coordination principle of distributed multi-energy systems," Energy, Elsevier, vol. 267(C).
    5. Liu, Hong & Zhao, Yue & Gu, Chenghong & Ge, Shaoyun & Yang, Zan, 2021. "Adjustable capability of the distributed energy system: Definition, framework, and evaluation model," Energy, Elsevier, vol. 222(C).
    6. Pahle, Michael & Schill, Wolf-Peter & Gambardella, Christian & Tietjen, Oliver, 2016. "Renewable Energy Support, Negative Prices, and Real-time Pricing," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 37, pages 147-169.
    7. Finck, Christian & Li, Rongling & Kramer, Rick & Zeiler, Wim, 2018. "Quantifying demand flexibility of power-to-heat and thermal energy storage in the control of building heating systems," Applied Energy, Elsevier, vol. 209(C), pages 409-425.
    8. Zhang, Sheng & Huang, Pei & Sun, Yongjun, 2016. "A multi-criterion renewable energy system design optimization for net zero energy buildings under uncertainties," Energy, Elsevier, vol. 94(C), pages 654-665.
    9. Zhang, Yang & Campana, Pietro Elia & Yang, Ying & Stridh, Bengt & Lundblad, Anders & Yan, Jinyue, 2018. "Energy flexibility from the consumer: Integrating local electricity and heat supplies in a building," Applied Energy, Elsevier, vol. 223(C), pages 430-442.
    10. Wang, Chaoyang & Zhao, Yongliang & Liu, Ming & Qiao, Yongqiang & Chong, Daotong & Yan, Junjie, 2018. "Peak shaving operational optimization of supercritical coal-fired power plants by revising control strategy for water-fuel ratio," Applied Energy, Elsevier, vol. 216(C), pages 212-223.
    11. Boßmann, Tobias & Eser, Eike Johannes, 2016. "Model-based assessment of demand-response measures—A comprehensive literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 57(C), pages 1637-1656.
    12. Monika Hall & Achim Geissler, 2020. "Load Control by Demand Side Management to Support Grid Stability in Building Clusters," Energies, MDPI, vol. 13(19), pages 1-15, October.
    13. Finck, Christian & Li, Rongling & Zeiler, Wim, 2019. "Economic model predictive control for demand flexibility of a residential building," Energy, Elsevier, vol. 176(C), pages 365-379.
    14. Cubi, Eduard & Doluweera, Ganesh & Bergerson, Joule, 2015. "Incorporation of electricity GHG emissions intensity variability into building environmental assessment," Applied Energy, Elsevier, vol. 159(C), pages 62-69.
    15. Vandermeulen, Annelies & van der Heijde, Bram & Helsen, Lieve, 2018. "Controlling district heating and cooling networks to unlock flexibility: A review," Energy, Elsevier, vol. 151(C), pages 103-115.
    16. Do, Linh Phuong Catherine & Lyócsa, Štefan & Molnár, Peter, 2021. "Residual electricity demand: An empirical investigation," Applied Energy, Elsevier, vol. 283(C).
    17. Niu, Jide & Tian, Zhe & Lu, Yakai & Zhao, Hongfang, 2019. "Flexible dispatch of a building energy system using building thermal storage and battery energy storage," Applied Energy, Elsevier, vol. 243(C), pages 274-287.
    18. Laurent Pagnier & Philippe Jacquod, 2017. "How fast can one overcome the paradox of the energy transition? A physico-economic model for the European power grid," Papers 1706.00330, arXiv.org, revised Jun 2018.
    19. Böttger, Diana & Götz, Mario & Theofilidi, Myrto & Bruckner, Thomas, 2015. "Control power provision with power-to-heat plants in systems with high shares of renewable energy sources – An illustrative analysis for Germany based on the use of electric boilers in district heatin," Energy, Elsevier, vol. 82(C), pages 157-167.
    20. Zhang, Sheng & Sun, Yongjun & Cheng, Yong & Huang, Pei & Oladokun, Majeed Olaide & Lin, Zhang, 2018. "Response-surface-model-based system sizing for Nearly/Net zero energy buildings under uncertainty," Applied Energy, Elsevier, vol. 228(C), pages 1020-1031.

    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:206:y:2017:i:c:p:22-31. 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.