IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v18y2021i13p6782-d581188.html
   My bibliography  Save this article

Operational Performance and Load Flexibility Analysis of Japanese Zero Energy House

Author

Listed:
  • Xiaoyi Zhang

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Fushun Road 11, Qingdao 266033, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

  • Weijun Gao

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Fushun Road 11, Qingdao 266033, China
    Faculty of Environmental Engineering, The University of Kitakyushu, Kitakyushu 808-0135, Japan)

  • Yanxue Li

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Fushun Road 11, Qingdao 266033, China)

  • Zixuan Wang

    (Innovation Institute for Sustainable Maritime Architecture Research and Technology, Qingdao University of Technology, Fushun Road 11, Qingdao 266033, China)

  • Yoshiaki Ushifusa

    (Faculty of Economics and Business Administration, The University of Kitakyushu, Kitakyushu 802-8577, Japan)

  • Yingjun Ruan

    (Institute of Mechanical Engineering, Tongji University, Siping Road 1239, Shanghai 200092, China)

Abstract

ZEHs (Zero Energy House) featuring energy-efficient designs and on-site renewable integration are being widely developed. This study introduced Japanese ZEHs with well-insulated thermal envelopes and investigated their detailed operational performances through on-site measurements and simulation models. Measurement data show that ZEHs effectively damped the variation of indoor air temperature compared to conventional houses, presenting great ability to retain inside heat energy, and are expected to potentially deliver energy flexibility as a virtual thermal energy storage medium. We developed a simplified thermal resistance–capacitance model for a house heating system; response behaviors were simulated under various scenarios. Results compared the variations of indoor temperature profiles and revealed the dependence of load flexibility on the building’s overall heat loss performance. We observed that overall heat loss rate played a crucial role in building heat energy storage efficiency; a well-insulated house shortened the heat-up time with less energy input, and extended the delayed period of indoor temperature under intermittent heating supply; a high set-point operative temperature and a low ambient temperature led to lower virtual thermal energy storage efficiency. The preheating strategy was simulated as an effective load-shifting approach in consuming surplus PV generation; approximately 50% of consumed PV generation could be shifted to replace grid import electricity for room heating during the occupied period.

Suggested Citation

  • Xiaoyi Zhang & Weijun Gao & Yanxue Li & Zixuan Wang & Yoshiaki Ushifusa & Yingjun Ruan, 2021. "Operational Performance and Load Flexibility Analysis of Japanese Zero Energy House," IJERPH, MDPI, vol. 18(13), pages 1-19, June.
  • Handle: RePEc:gam:jijerp:v:18:y:2021:i:13:p:6782-:d:581188
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/18/13/6782/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1660-4601/18/13/6782/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ansarin, Mohammad & Ghiassi-Farrokhfal, Yashar & Ketter, Wolfgang & Collins, John, 2020. "The economic consequences of electricity tariff design in a renewable energy era," Applied Energy, Elsevier, vol. 275(C).
    2. Le Dréau, J. & Heiselberg, P., 2016. "Energy flexibility of residential buildings using short term heat storage in the thermal mass," Energy, Elsevier, vol. 111(C), pages 991-1002.
    3. Li, Pei-Hao & Pye, Steve, 2018. "Assessing the benefits of demand-side flexibility in residential and transport sectors from an integrated energy systems perspective," Applied Energy, Elsevier, vol. 228(C), pages 965-979.
    4. Wang, Huilong & Wang, Shengwei & Tang, Rui, 2019. "Development of grid-responsive buildings: Opportunities, challenges, capabilities and applications of HVAC systems in non-residential buildings in providing ancillary services by fast demand responses," Applied Energy, Elsevier, vol. 250(C), pages 697-712.
    5. Jin, Xiaolong & Mu, Yunfei & Jia, Hongjie & Wu, Jianzhong & Jiang, Tao & Yu, Xiaodan, 2017. "Dynamic economic dispatch of a hybrid energy microgrid considering building based virtual energy storage system," Applied Energy, Elsevier, vol. 194(C), pages 386-398.
    6. Li, Yanxue & Zhang, Xiaoyi & Gao, Weijun & Ruan, Yingjun, 2020. "Capacity credit and market value analysis of photovoltaic integration considering grid flexibility requirements," Renewable Energy, Elsevier, vol. 159(C), pages 908-919.
    7. Ghiaus, Christian & Ahmad, Naveed, 2020. "Thermal circuits assembling and state-space extraction for modelling heat transfer in buildings," Energy, Elsevier, vol. 195(C).
    8. Barone, Giovanni & Buonomano, Annamaria & Forzano, Cesare & Giuzio, Giovanni Francesco & Palombo, Adolfo, 2020. "Increasing self-consumption of renewable energy through the Building to Vehicle to Building approach applied to multiple users connected in a virtual micro-grid," Renewable Energy, Elsevier, vol. 159(C), pages 1165-1176.
    9. Harder, Nick & Qussous, Ramiz & Weidlich, Anke, 2020. "The cost of providing operational flexibility from distributed energy resources," Applied Energy, Elsevier, vol. 279(C).
    10. 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.
    11. Vieira, Filomeno M. & Moura, Pedro S. & de Almeida, Aníbal T., 2017. "Energy storage system for self-consumption of photovoltaic energy in residential zero energy buildings," Renewable Energy, Elsevier, vol. 103(C), pages 308-320.
    12. Wang, Ran & Feng, Wei & Wang, Lan & Lu, Shilei, 2021. "A comprehensive evaluation of zero energy buildings in cold regions: Actual performance and key technologies of cases from China, the US, and the European Union," Energy, Elsevier, vol. 215(PA).
    13. Junker, Rune Grønborg & Azar, Armin Ghasem & Lopes, Rui Amaral & Lindberg, Karen Byskov & Reynders, Glenn & Relan, Rishi & Madsen, Henrik, 2018. "Characterizing the energy flexibility of buildings and districts," Applied Energy, Elsevier, vol. 225(C), pages 175-182.
    14. Pol Olivella-Rosell & Pau Lloret-Gallego & Íngrid Munné-Collado & Roberto Villafafila-Robles & Andreas Sumper & Stig Ødegaard Ottessen & Jayaprakash Rajasekharan & Bernt A. Bremdal, 2018. "Local Flexibility Market Design for Aggregators Providing Multiple Flexibility Services at Distribution Network Level," Energies, MDPI, vol. 11(4), pages 1-19, April.
    15. De Coninck, Roel & Helsen, Lieve, 2016. "Quantification of flexibility in buildings by cost curves – Methodology and application," Applied Energy, Elsevier, vol. 162(C), pages 653-665.
    16. Michael Short & Sergio Rodriguez & Richard Charlesworth & Tracey Crosbie & Nashwan Dawood, 2019. "Optimal Dispatch of Aggregated HVAC Units for Demand Response: An Industry 4.0 Approach," Energies, MDPI, vol. 12(22), pages 1-20, November.
    17. Schill, Wolf-Peter & Zerrahn, Alexander, 2020. "Flexible electricity use for heating in markets with renewable energy," EconStor Open Access Articles and Book Chapters, ZBW - Leibniz Information Centre for Economics, vol. 266.
    18. Georges, Emeline & Cornélusse, Bertrand & Ernst, Damien & Lemort, Vincent & Mathieu, Sébastien, 2017. "Residential heat pump as flexible load for direct control service with parametrized duration and rebound effect," Applied Energy, Elsevier, vol. 187(C), pages 140-153.
    19. 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.
    20. Oliveira Panão, Marta J.N. & Mateus, Nuno M. & Carrilho da Graça, G., 2019. "Measured and modeled performance of internal mass as a thermal energy battery for energy flexible residential buildings," Applied Energy, Elsevier, vol. 239(C), pages 252-267.
    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. Li, Yanxue & Wang, Zixuan & Xu, Wenya & Gao, Weijun & Xu, Yang & Xiao, Fu, 2023. "Modeling and energy dynamic control for a ZEH via hybrid model-based deep reinforcement learning," Energy, Elsevier, vol. 277(C).
    2. Wang, Zixuan & Xiao, Fu & Ran, Yi & Li, Yanxue & Xu, Yang, 2024. "Scalable energy management approach of residential hybrid energy system using multi-agent deep reinforcement learning," Applied Energy, Elsevier, vol. 367(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. 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. Bampoulas, Adamantios & Saffari, Mohammad & Pallonetto, Fabiano & Mangina, Eleni & Finn, Donal P., 2021. "A fundamental unified framework to quantify and characterise energy flexibility of residential buildings with multiple electrical and thermal energy systems," Applied Energy, Elsevier, vol. 282(PA).
    4. Massimiliano Manfren & Maurizio Sibilla & Lamberto Tronchin, 2021. "Energy Modelling and Analytics in the Built Environment—A Review of Their Role for Energy Transitions in the Construction Sector," Energies, MDPI, vol. 14(3), pages 1-29, January.
    5. 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.
    6. Chen, Yongbao & Chen, Zhe & Xu, Peng & Li, Weilin & Sha, Huajing & Yang, Zhiwei & Li, Guowen & Hu, Chonghe, 2019. "Quantification of electricity flexibility in demand response: Office building case study," Energy, Elsevier, vol. 188(C).
    7. Guo, Yurun & Wang, Shugang & Wang, Jihong & Zhang, Tengfei & Ma, Zhenjun & Jiang, Shuang, 2024. "Key district heating technologies for building energy flexibility: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 189(PB).
    8. Ziras, Charalampos & Heinrich, Carsten & Pertl, Michael & Bindner, Henrik W., 2019. "Experimental flexibility identification of aggregated residential thermal loads using behind-the-meter data," Applied Energy, Elsevier, vol. 242(C), pages 1407-1421.
    9. 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.
    10. Bampoulas, Adamantios & Pallonetto, Fabiano & Mangina, Eleni & Finn, Donal P., 2022. "An ensemble learning-based framework for assessing the energy flexibility of residential buildings with multicomponent energy systems," Applied Energy, Elsevier, vol. 315(C).
    11. Tang, Hong & Wang, Shengwei & Li, Hangxin, 2021. "Flexibility categorization, sources, capabilities and technologies for energy-flexible and grid-responsive buildings: State-of-the-art and future perspective," Energy, Elsevier, vol. 219(C).
    12. 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.
    13. Arteconi, Alessia & Mugnini, Alice & Polonara, Fabio, 2019. "Energy flexible buildings: A methodology for rating the flexibility performance of buildings with electric heating and cooling systems," Applied Energy, Elsevier, vol. 251(C), pages 1-1.
    14. Harder, Nick & Qussous, Ramiz & Weidlich, Anke, 2020. "The cost of providing operational flexibility from distributed energy resources," Applied Energy, Elsevier, vol. 279(C).
    15. 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.
    16. Silvia Erba & Lorenzo Pagliano, 2021. "Combining Sufficiency, Efficiency and Flexibility to Achieve Positive Energy Districts Targets," Energies, MDPI, vol. 14(15), pages 1-32, August.
    17. Kumar, Gokula Manikandan Senthil & Cao, Sunliang, 2023. "Leveraging energy flexibilities for enhancing the cost-effectiveness and grid-responsiveness of net-zero-energy metro railway and station systems," Applied Energy, Elsevier, vol. 333(C).
    18. Wanapinit, Natapon & Thomsen, Jessica & Weidlich, Anke, 2022. "Integrating flexibility provision into operation planning: A generic framework to assess potentials and bid prices of end-users," Energy, Elsevier, vol. 261(PB).
    19. Amadeh, Ali & Lee, Zachary E. & Zhang, K. Max, 2022. "Quantifying demand flexibility of building energy systems under uncertainty," Energy, Elsevier, vol. 246(C).
    20. 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).

    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:gam:jijerp:v:18:y:2021:i:13:p:6782-:d:581188. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.