IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v221y2018icp180-194.html
   My bibliography  Save this article

Optimal demand charge reduction for commercial buildings through a combination of efficiency and flexibility measures

Author

Listed:
  • Zhang, Yuna
  • Augenbroe, Godfried

Abstract

A substantial part of electricity bills in commercial buildings can consist of demand charges. Lowering the peak power and/or reducing the hours that a power threshold is exceeded can drastically reduce demand charges. The ability to do so by dynamic, operational adjustments reflects the “energy flexibility” of the building. This paper targets the optimal combination of design and operational measures in a retrofit or new design project that delivers the most effective way of reducing demand charges by increasing energy flexibility and efficiency of commercial buildings. This goal is achieved through an analysis of all feasible energy consumption and peak reduction measures in different building types and in different use contexts. A search algorithm that compares all possible interventions will deliver the optimum. This leads to a stochastic optimization approach with recognition of the effects of all possible sources of uncertainty. This paper evaluates the measures that are commonly adopted to decrease energy consumption and increase energy flexibility, including (1) upgrading building components and installing energy efficient equipment; (2) applying dynamic building load control strategies; (3) installing a rooftop photovoltaic panel array. Operational interventions include the manipulation of thermostat settings and the voltage reduction of lighting and appliances (in some cases including HVAC components) in the building, which may cause some level of thermal and visual discomfort during certain periods. In order to support retrofit and design improvement decisions, an approach is developed to find the optimal mix of measures that maximize the net present value of the investment in all measures over twenty years for the owner. This paper analyzes the optimal solutions for three commercial building types, office, hospital, and retail. The paper suggests a modeling and optimization framework that can be used by building designers and operators to make optimal investment decisions to reduce demand charges. The paper shows a novel support of the decision making by building operators when faced with the opportunity to reduce demand charges.

Suggested Citation

  • Zhang, Yuna & Augenbroe, Godfried, 2018. "Optimal demand charge reduction for commercial buildings through a combination of efficiency and flexibility measures," Applied Energy, Elsevier, vol. 221(C), pages 180-194.
  • Handle: RePEc:eee:appene:v:221:y:2018:i:c:p:180-194
    DOI: 10.1016/j.apenergy.2018.03.150
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261918304951
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2018.03.150?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. Di Somma, M. & Graditi, G. & Heydarian-Forushani, E. & Shafie-khah, M. & Siano, P., 2018. "Stochastic optimal scheduling of distributed energy resources with renewables considering economic and environmental aspects," Renewable Energy, Elsevier, vol. 116(PA), pages 272-287.
    2. van Staden, Adam Jacobus & Zhang, Jiangfeng & Xia, Xiaohua, 2011. "A model predictive control strategy for load shifting in a water pumping scheme with maximum demand charges," Applied Energy, Elsevier, vol. 88(12), pages 4785-4794.
    3. Nuytten, Thomas & Claessens, Bert & Paredis, Kristof & Van Bael, Johan & Six, Daan, 2013. "Flexibility of a combined heat and power system with thermal energy storage for district heating," Applied Energy, Elsevier, vol. 104(C), pages 583-591.
    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. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    6. 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.
    7. George B. Dantzig, 1955. "Linear Programming under Uncertainty," Management Science, INFORMS, vol. 1(3-4), pages 197-206, 04-07.
    8. Cristina Carletti & Fabio Sciurpi & Leone Pierangioli, 2014. "The Energy Upgrading of Existing Buildings: Window and Shading Device Typologies for Energy Efficiency Refurbishment," Sustainability, MDPI, vol. 6(8), pages 1-24, August.
    9. Denholm, Paul & Hand, Maureen, 2011. "Grid flexibility and storage required to achieve very high penetration of variable renewable electricity," Energy Policy, Elsevier, vol. 39(3), pages 1817-1830, March.
    10. Sadineni, Suresh B. & Boehm, Robert F., 2012. "Measurements and simulations for peak electrical load reduction in cooling dominated climate," Energy, Elsevier, vol. 37(1), pages 689-697.
    11. Wang, Qinpeng & Augenbroe, Godfried & Kim, Ji-Hyun & Gu, Li, 2016. "Meta-modeling of occupancy variables and analysis of their impact on energy outcomes of office buildings," Applied Energy, Elsevier, vol. 174(C), pages 166-180.
    12. 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. Wengang Chen & Jiajia Chen & Bingyin Xu & Xinpeng Cong & Wenliang Yin, 2023. "Optimal Configuration of User-Side Energy Storage for Multi-Transformer Integrated Industrial Park Microgrid," Energies, MDPI, vol. 16(7), pages 1-15, March.
    2. Liu, Mingzhe & Heiselberg, Per, 2019. "Energy flexibility of a nearly zero-energy building with weather predictive control on a convective building energy system and evaluated with different metrics," Applied Energy, Elsevier, vol. 233, pages 764-775.
    3. Khalilpour, Kaveh R. & Lusis, Peter, 2020. "Network capacity charge for sustainability and energy equity: A model-based analysis," Applied Energy, Elsevier, vol. 266(C).
    4. Gržanić, M. & Capuder, T. & Zhang, N. & Huang, W., 2022. "Prosumers as active market participants: A systematic review of evolution of opportunities, models and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 154(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. 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).
    2. 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.
    3. Harder, Nick & Qussous, Ramiz & Weidlich, Anke, 2020. "The cost of providing operational flexibility from distributed energy resources," Applied Energy, Elsevier, vol. 279(C).
    4. Lund, Peter D. & Lindgren, Juuso & Mikkola, Jani & Salpakari, Jyri, 2015. "Review of energy system flexibility measures to enable high levels of variable renewable electricity," Renewable and Sustainable Energy Reviews, Elsevier, vol. 45(C), pages 785-807.
    5. Guerra, K. & Haro, P. & Gutiérrez, R.E. & Gómez-Barea, A., 2022. "Facing the high share of variable renewable energy in the power system: Flexibility and stability requirements," Applied Energy, Elsevier, vol. 310(C).
    6. Clarke, Fiona & Dorneanu, Bogdan & Mechleri, Evgenia & Arellano-Garcia, Harvey, 2021. "Optimal design of heating and cooling pipeline networks for residential distributed energy resource systems," Energy, Elsevier, vol. 235(C).
    7. Brunner, Christoph & Deac, Gerda & Braun, Sebastian & Zöphel, Christoph, 2020. "The future need for flexibility and the impact of fluctuating renewable power generation," Renewable Energy, Elsevier, vol. 149(C), pages 1314-1324.
    8. Min, C.G. & Park, J.K. & Hur, D. & Kim, M.K., 2016. "A risk evaluation method for ramping capability shortage in power systems," Energy, Elsevier, vol. 113(C), pages 1316-1324.
    9. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Xu, Wenya & Wang, Zixuan, 2022. "Operational performance and grid-support assessment of distributed flexibility practices among residential prosumers under high PV penetration," Energy, Elsevier, vol. 238(PB).
    10. Andrychowicz, Mateusz & Olek, Blazej & Przybylski, Jakub, 2017. "Review of the methods for evaluation of renewable energy sources penetration and ramping used in the Scenario Outlook and Adequacy Forecast 2015. Case study for Poland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 74(C), pages 703-714.
    11. Mararakanye, Ndamulelo & Bekker, Bernard, 2019. "Renewable energy integration impacts within the context of generator type, penetration level and grid characteristics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 108(C), pages 441-451.
    12. Sinn, Hans-Werner, 2017. "Buffering volatility: A study on the limits of Germany's energy revolution," European Economic Review, Elsevier, vol. 99(C), pages 130-150.
    13. 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).
    14. Golmohamadi, Hessam & Larsen, Kim Guldstrand & Jensen, Peter Gjøl & Hasrat, Imran Riaz, 2022. "Integration of flexibility potentials of district heating systems into electricity markets: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 159(C).
    15. Chang-Gi Min & Mun-Kyeom Kim, 2017. "Flexibility-Based Evaluation of Variable Generation Acceptability in Korean Power System," Energies, MDPI, vol. 10(6), pages 1-12, June.
    16. Batas Bjelić, Ilija & Rajaković, Nikola & Krajačić, Goran & Duić, Neven, 2016. "Two methods for decreasing the flexibility gap in national energy systems," Energy, Elsevier, vol. 115(P3), pages 1701-1709.
    17. McPherson, Madeleine & Karney, Bryan, 2017. "A scenario based approach to designing electricity grids with high variable renewable energy penetrations in Ontario, Canada: Development and application of the SILVER model," Energy, Elsevier, vol. 138(C), pages 185-196.
    18. Kopiske, Jakob & Spieker, Sebastian & Tsatsaronis, George, 2017. "Value of power plant flexibility in power systems with high shares of variable renewables: A scenario outlook for Germany 2035," Energy, Elsevier, vol. 137(C), pages 823-833.
    19. Teirilä, Juha, 2020. "The value of the nuclear power plant fleet in the German power market under the expansion of fluctuating renewables," Energy Policy, Elsevier, vol. 136(C).
    20. Zhang, Chong & Xue, Xue & Du, Qianzhou & Luo, Yimo & Gang, Wenjie, 2019. "Study on the performance of distributed energy systems based on historical loads considering parameter uncertainties for decision making," Energy, Elsevier, vol. 176(C), pages 778-791.

    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:221:y:2018:i:c:p:180-194. 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.