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Energy flexible buildings: A methodology for rating the flexibility performance of buildings with electric heating and cooling systems

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  • Arteconi, Alessia
  • Mugnini, Alice
  • Polonara, Fabio

Abstract

In the present energy scenario, buildings are playing more and more as energy prosumers. They can use and produce energy and also actively manage their energy demand. The energy flexibility quantifies their potential to adjust the energy demand on the basis of external requests. The objective of this paper is to propose a method for buildings energy flexibility labelling at design conditions in the same fashion as the energy performance label. The flexibility quantification is based on the calculation of four flexibility parameters, which contribute to the definition of the Flexibility Performance Indicator. In order to assess the Flexibility Performance Indicator, buildings dynamic simulations are necessary and the boundary conditions (i.e. demand response event, representative day, comfort constraints) to be considered during the evaluation are provided as part of the proposed methodology. The method was applied to different Italian buildings, which differ for geographic location and design specifications and, in particular, the effects of building structure, heating/cooling systems and energy storage systems were compared. Results show that the climatic conditions affect the flexibility performance, while the building feature more relevant is the thermal mass of the building envelope, more than that provided by the distribution system. A sensitivity analysis to evaluate how the results are influenced by the proposed boundary conditions was also performed. Their choice confirms to have a relevant impact on flexibility quantification, then their unique definition has a paramount importance within this methodology.

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  • 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.
  • Handle: RePEc:eee:appene:v:251:y:2019:i:c:100
    DOI: 10.1016/j.apenergy.2019.113387
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    14. Sara Sultan & Jason Hirschey & Navin Kumar & Borui Cui & Xiaobing Liu & Tim J. LaClair & Kyle R. Gluesenkamp, 2023. "Techno-Economic Assessment of Residential Heat Pump Integrated with Thermal Energy Storage," Energies, MDPI, vol. 16(10), pages 1-23, May.
    15. Verhaeghe, C. & Verbeke, S. & Audenaert, A., 2021. "A consistent taxonomic framework: towards common understanding of high energy performance building definitions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 146(C).
    16. Li, Han & Johra, Hicham & de Andrade Pereira, Flavia & Hong, Tianzhen & Le Dréau, Jérôme & Maturo, Anthony & Wei, Mingjun & Liu, Yapan & Saberi-Derakhtenjani, Ali & Nagy, Zoltan & Marszal-Pomianowska,, 2023. "Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives," Applied Energy, Elsevier, vol. 343(C).
    17. Gallardo, Andres & Berardi, Umberto, 2022. "Evaluation of the energy flexibility potential of radiant ceiling panels with thermal energy storage," Energy, Elsevier, vol. 254(PC).
    18. Song, Yuguang & Xia, Mingchao & Chen, Qifang & Chen, Fangjian, 2023. "A data-model fusion dispatch strategy for the building energy flexibility based on the digital twin," Applied Energy, Elsevier, vol. 332(C).
    19. 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).
    20. Coccia, Gianluca & Mugnini, Alice & Polonara, Fabio & Arteconi, Alessia, 2021. "Artificial-neural-network-based model predictive control to exploit energy flexibility in multi-energy systems comprising district cooling," Energy, Elsevier, vol. 222(C).
    21. Yan Cao & Towhid Pourrostam & Yousef Zandi & Nebojša Denić & Bogdan Ćirković & Alireza Sadighi Agdas & Abdellatif Selmi & Vuk Vujović & Kittisak Jermsittiparsert & Momir Milic, 2021. "RETRACTED ARTICLE: Analyzing the energy performance of buildings by neuro-fuzzy logic based on different factors," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(12), pages 17349-17373, December.
    22. Ali Saberi Derakhtenjani & Andreas K. Athienitis, 2021. "Model Predictive Control Strategies to Activate the Energy Flexibility for Zones with Hydronic Radiant Systems," Energies, MDPI, vol. 14(4), pages 1-19, February.
    23. Ilaria Vigna & Roberta Pernetti & Giovanni Pernigotto & Andrea Gasparella, 2020. "Analysis of the Building Smart Readiness Indicator Calculation: A Comparative Case-Study with Two Panels of Experts," Energies, MDPI, vol. 13(11), pages 1-18, June.
    24. Jenny Crawley & Despina Manouseli & Peter Mallaburn & Cliff Elwell, 2022. "An Empirical Energy Demand Flexibility Metric for Residential Properties," Energies, MDPI, vol. 15(14), pages 1-18, July.
    25. Zhu, Jie & Niu, Jide & Tian, Zhe & Zhou, Ruoyu & Ye, Chuang, 2022. "Rapid quantification of demand response potential of building HAVC system via data-driven model," Applied Energy, Elsevier, vol. 325(C).

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