[1] H. Yuan, & Tang, W., Flexibility Provision From Urban Buildings to Low-Carbon Power Systems: Quantification, Aggregation and System Integration, IET Energy Systems Integration, 7(1) (2025) e70017.
[2] IEA, World Energy Outlook 2023, IEA, Paris, 2023.
[3] S.G. Cai, Zhonghua, Defining the energy role of buildings as flexumers: A review of definitions, technologies, and applications, Energy and Buildings, 311 (2024) 113821.
[4] A.J. Marszal, et al., Zero Energy Building definitions, Energy and Buildings, 43 (2011) 971-979.
[5] M.S. Lu, Yongjun; Kokogiannakis, Georgios; Ma, Zhenjun, Design of Flexible Energy Systems for Nearly/Net Zero Energy Buildings Under Uncertainty Characteristics: A Review, Renewable and Sustainable Energy Reviews, 205 (2024) 114828.
[6] Z. Yang, Kong, D., Chen, Z., Zhang, Z., Du, D., & Zhu, Z., A Data-Driven Battery Energy Storage Regulation Approach Integrating Machine Learning Forecasting Models for Enhancing Building Energy Flexibility-A Case Study of a Net-Zero Carbon Building in China. , Buildings, 15(19) (2025) 3611.
[7] V. Rezaee, & Masoumnezhad, M., Study of the impact of thermal mass changes on the thermal comfort of buildings in Irans climates using the Köppen-Geiger method, Amirkabir Journal of Mechanical Engineering, 57(8) (2025) 989-1012.
[8] C. Finck, et al. , Review of applied and tested control possibilities for energy flexibility in buildings, Energy Reports, 6 (2020) 709-718.
[9] Y.E. Himeur, Mariam; Fadli, Fodil; Meskin, Nader; Petri, Ioan; Rezgui, Yacine; Bensaali, Faycal; Amira, Abbes, AI-big data analytics for building automation and management systems: A survey, actual challenges and future perspectives, Artificial Intelligence Review, 56(6) (2023) 4929–5021.
[10] A. Arteconi, & Polonara, F., Assessing the demand side management potential and the energy flexibility of heat pumps in buildings, Energies, 11(9) (2018) 2346.
[11] K. Le, et al., A review of reinforcement learning for building energy flexibility, Energy and AI, 12 (2023) 100228.
[12] S.W. Yang, Man Pun; Ng, Bing Feng; Dubey, Swapnil; Henze, Gregor P.; Chen, Wanyu; Baskaran, Krishnamoorthy, Model Predictive Control for Integrated Control of Air-Conditioning and Mechanical Ventilation, Lighting and Shading Systems, Applied Energy, 297 (2021) 117112.
[13] G.F. Li, Yangyang; Pertzborn, Amanda; O'Neill, Zheng; Wen, Jin, Demand Flexibility Evaluation for Building Energy Systems with Active Thermal Storage Using Model Predictive Control, in: 2022 ASHRAE Annual Conference, 2022, pp. 650–658.
[14] B.D. Cui, Jin; Lee, Seungjae; Im, Piljae; Salonvaara, Mikael; Hun, Diana; Shrestha, Som, Model Predictive Control for Active Insulation in Building Envelopes, Energy and Buildings, 267 (2022) 112108.
[15] J. Clauß, Brozovsky, J., & Georges, L., Demonstrating the load-shifting potential of a schedule-based control in a real-life educational building, Energy and Buildings, 316 (2024) 114321.
[16] H. Li, Johra, H., de Andrade Pereira, F., Hong, T., Le Dréau, J., Maturo, A., Wei, M., Liu, Y., Saberi-Derakhtenjani, A., Nagy, Z., Marszal-Pomianowska, A., Finn, D., Miyata, S., Kaspar, K., Nweye, K., O'Neill, Z., Pallonetto, F., & Dong, B., Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives, Applied Energy, 343 (2023) 121217.
[17] J. Le Dréau, Lopes, R. A., O'Connell, S., Finn, D., Hu, M., Queiroz, H., Alexander, D., Satchwell, A., Österreicher, D., Polly, B., et al., Developing energy flexibility in clusters of buildings: A critical analysis of barriers from planning to operation, Energy and Buildings, 300 (2023) 113608.
[18] Y.F. Ye, Cary A.; Xu, Rong; Huang, Sen; Liu, Yuan; Vrabie, Draguna; Zhang, Jian; Zuo, Wangda, System Modeling for Grid-Interactive Efficient Building Applications, Journal of Building Engineering, 69 (2023) 106148.
[19] Y.P. Fu, Amanda; O'Neill, Zheng; Bushby, Steven T.; Wen, Jin, Utilizing Commercial Heating, Ventilating, and Air Conditioning Systems to Provide Grid Services: A Review, Applied Energy, 307 (2022) 118133.
[20] L. Zhang, Huo, M., Zhou, T., Pan, J., & Xu, Y., Energy Flexibility Realization in Grid-Interactive Buildings for Demand Response: State-of-the-Art Review on Strategies, Resources, Control, and KPIs, Energies, 18(18) (2025) 4960.
[21] G. Li, Ren, L., Fu, Y., Yang, Z., et al., A critical review of cyber-physical security for building automation systems, Annual Reviews in Control, 55 (2023) 237-254.
[22] A. Llaria, Dos Santos, J., Terrasson, G., Boussaada, Z., Merlo, C., & Curea, O., Intelligent Buildings in Smart Grids: A Survey on Security and Privacy Issues Related to Energy Management, Energies, 14(9) (2021) 2733.
[23] Z. Liu, Zhang, X., Sun, Y., & Zhou, Y., Advanced controls on energy reliability, flexibility and occupant-centric control for smart and energy-efficient buildings, Energy and Buildings, 297 (2023) 113436.
[24] O. Vera-Piazzini, & Scarpa, M., Building energy model calibration: A review of the state of the art in approaches, methods, and tools, Journal of Building Engineering, 86 (2024) 108287.
[25] V.F. Mendes, A.S. Cruz, A.P. Gomes, J.C. Mendes, A systematic review of methods for evaluating the thermal performance of buildings through energy simulations, Renewable and Sustainable Energy Reviews, 198 (2024) 113875.
[26] O. Ahmed, N. Sezer, M. Ou, L.L. Wang, I.G. Hassan, State-of-the-art review of occupant behavior modeling and implementation in building performance simulation, Renewable and Sustainable Energy Reviews, 185 (2023) 113558.
[27] J. Le Dréau, Lopes, R. A., O'Connell, S., Finn, D., Hu, M., Queiroz, H., et al., Developing energy flexibility in clusters of buildings: A critical analysis of barriers from planning to operation, Energy and Buildings, 300 (2023) 113608.
[28] H. Li, Johra, H., de Andrade Pereira, F., Hong, T., Le Dréau, J., Maturo, A., et al., Data-driven key performance indicators and datasets for building energy flexibility: A review and perspectives, Applied Energy, 343 (2023) 121217.
[29] Z. Afroz, Wu, H., Sethuvenkatraman, S., Henze, G., Junker, R. G., & Shepit, M., A study on price responsive energy flexibility of an office building under cooling dominated climatic conditions, Energy and Buildings, 316 (2024) 114359.
[30] A.J. Marszal, et al., Zero Energy Building--A review of definitions and calculation methodologies, Energy and Buildings, 43(4) (2011) 971-979.
[31] S.Ø. Jensen, et al., IEA EBC Annex 67: Energy Flexible Buildings, Energy Procedia, 2017.
[32] J. Salom, A.J. Marszal, J. Widén, J. Candanedo, K.B. Lindberg, Analysis of load match and grid interaction indicators in net zero energy buildings with simulated and monitored data, Applied Energy, 136 (2014) 119-131.
[33] M. Masoumnezhad, M. Tehrani, A. Akoushideh, N. Narimanzadeh, A new adaptive fuzzy hybrid unscented Kalman/Hâinfinity filter for state estimating dynamical systems, IET Signal Processing, 15(7) (2021) 459-466.
[34] A.A. Bakar, Yussof, S., Ghapar, A. A., Sameon, S. S., & Jørgensen, B. N., A Review of Privacy Concerns in Energy-Efficient Smart Buildings: Risks, Rights, and Regulations, Energies, 17(5) (2024) 977.
[35] M. de-Borja-Torrejon, Mor, G., Cipriano, J., Leon-Rodriguez, A.-L., Auer, T., & Crawley, J., Closing the energy flexibility gap: Enriching flexibility performance rating of buildings with monitored data, Energy and Buildings, 311 (2024) 114141.
[36] K. Sirviö, S. Motta, K. Rauma, C. Evens, Multi-level functional analysis of developing prosumers and energy communities with value creation framework, Applied Energy, 368 (2024) 123496.
[37] I.R. Diamond, Grant, R. C., Feldman, B. M., et al. , Defining consensus: A systematic review recommends methodologic criteria for reporting of Delphi studies, Journal of Clinical Epidemiology, 67(4) (2014) 401-409.
[38] C. Okoli, & Pawlowski, S. D., The Delphi method as a research tool: An example, design considerations and applications, Information & Management, 42(1) (2004) 15-29.
[39] B. Mataloto, Ferreira, J. C., & Cruz, N., LoBEMS—IoT for Building and Energy Management Systems, Electronics, 8(7) (2019) 763.
[40] M. Poyyamozhi, Murugesan, B., Rajamanickam, N., Shorfuzzaman, M., & Aboelmagd, Y., IoT—A Promising Solution to Energy Management in Smart Buildings: A Systematic Review, Applications, Barriers, and Future Scope, Buildings, 14(11) (2024) 3446.
[41] W. Li, Koo, C., Cha, S. H., Lai, J. H. K., & Lee, J., A conceptual framework for the real-time monitoring and diagnostic system for the optimal operation of smart building: A case study in Hotel ICON of Hong Kong, Energy Procedia, 158 (2019) 3107-3112.
[42] V. Rezaee, Taghizadeh, A., & Masoumnezhad, M. , Comparative Feasibility Study of Two Direct Expansion Solar Water Heater Heat Pump Systems in Rasht Climate, Amirkabir Journal of Mechanical Engineering, 57(5) (2025) 589-610.
[43] W. Liang, Li, H., Zhan, S., Chong, A., & Hong, T., Energy flexibility quantification of a tropical net-zero office building using physically consistent neural network-based model predictive control, Advances in Applied Energy, 14 (2024) 100167.