Publications

[B1] Hu, M., & Tang, R. (2025). Energy Flexible Buildings in Local Energy Systems. In Digitalisation of Local Energy Systems (pp. 169–217). Springer Nature Switzerland. PDFDOI

[J39] Dan, Z., Zheng, Y., Li, Y., Song, A., Qiu, Y. L., Zhu, Y., Fan, C., Liu, Z., Shen, P., Hu, M., Lee, S., & Zhou, Y. (2027). A city-scale modelling framework for equitable EV charging station planning using the comprehensive charging duration metric. Applied Energy, 427, 128953. PDFDOI

[J38] Ma, Z., Lu, M., Yang, X., Hu, M., et al. (2026). Delivering building demand flexibility for grid-interactive operation: from perception and cognition to decision, execution, and verification. Applied Energy, 426, 128668. PDFDOI

[J37] Li, Q., Hu, M., Ma, R., Chen, J., & Luo, X. (2026). Temporal graph convolutional networks with morphological adjacency matrix: microclimate prediction for building energy modeling. Energy and Buildings, 369, 118051. PDFDOI

[J36] Li, Q., Hu, M., Wang, W., Chen, J., & Luo, X. (2026). A hybrid physics-based and data-driven framework for spatiotemporal prediction of urban microclimate across climate zones. Building and Environment, 304, 115000. PDFDOI

[J35] Zhang, J., Wang, Z., Ma, T., Zhang, H., Xu, K., Li, A., Hu, M., & Xiao, F. (2026). Data-driven characterization of spatio-temporal correlations between AC terminals and occupied zones for zone-based control in large built environments. Building and Environment, 304, 114982. PDFDOI

[J34] Bayer, D. R., Hu, M., Miller, C., & Pruckner, M. (2026). Optimizing Heat Pump and Electric Vehicle Flexibility through Predictive Home Energy Management Systems within Urban Energy Digital Twins. Energy and Buildings, 367, 117674. PDFDOI

[J33] Jie, P., Tian, S., Liu, P., Wang, J., Santamouris, M., Hu, M., & Shi, X. (2026). Microclimate-Integrated Urban Building Energy Modeling (MUBEM): Spatiotemporal analysis of climate-driven energy use in Shanghai and Singapore. Building and Environment, 301, 114749. PDFDOI

[J32] Tang, H., Zou, W., Dai, M., Wang, S., & Hu, M. (2026). Multi-timescale rolling optimization coordinating heterogeneous EV and building load flexibility in community energy systems with NGBoost-based renewable forecast. Applied Energy, 415, 127924. PDFDOI

[J31] Xu, L., Lei, S., Hu, M., Srinivasan, D., & Song, Z. (2026). Proactive grid investment enables V2G for 100% adoption of electric vehicles in urban areas. Joule, 10, 102393. PDFDOINewsCover

[J30] Liu, W., Tian, Z., Hu, M., Li, J., Ma, L., & Chen, X. (2026). BIPVs as an energy-resilient pathway for decarbonizing high-density island cities. Cell Reports Sustainability, 3, 100682. PDFDOI

[J29] Shen, X., Hu, M., Zhou, X., Yan, D., & An, J. (2026). Integrated parametric design of ventilation corridors and urban form for enhanced urban ventilation performance. Building Simulation, 19, 761–787. PDFDOI

[J28] Chen, S., Zhang, Q., Hu, M., Zhai, J., Li, J., & Guo, Z. (2026). Double-layer multi-objective optimization for combined cooling and waste heat recovery systems in data centers. Energy Conversion and Management, 356, 121349. PDFDOI

[J27] Jie, P., Li, G., Wang, J., Santamouris, M., Du, S., Zhu, S., Yue, H., Feng, G., Hu, M., & Shi, X. (2026). WRF-based hybrid model for high-resolution prediction of urban thermal-wind environments under present and future climate scenarios. Sustainable Cities and Society, 142, 107315. PDFDOICode

[J26] Zhang, C., Zhong, W., Li, K., Hu, M., Zheng, H., & Zhang, T. (2026). Surrogate model-based design optimization of modular façades under multifunctional scenarios. Building and Environment, 295, 114475. PDFDOI

[J25] Hu, M., Benson, S., & de Chalendar, J. A. (2026). Characterization and modeling of building dynamic thermal responses to demand response strategies using large-scale in-situ measurements. Energy and Buildings, 354, 116957. PDFDOI

[J24] Gu, H., Jin, X., Xiao, F., Hu, M., & Miller, C. (2025). An ex-post analysis framework for assessing the effectiveness and driving factors of green building certification adoption: A case study of Singapore. Energy and Buildings, 351, 116733. PDFDOI

[J23] Saeed, M. H., Hu, M., Kazmi, H., & Deconinck, G. (2025). ScaleONet: Scalable and control-oriented modeling of building cluster thermal dynamics using deep operator networks — A practical case study for a Belgian district. Energy and AI, 22, 100634. PDFDOI

[J22] Li, Q., Luo, X., & Hu, M. (2025). Impact of seasonal wind and building morphology on microclimate and building energy consumption. Building Simulation, 18, 3133–3152. PDFDOI

[J21] Wang, H., Tan, Z., Mo, J., Hu, M., Ji, Y., & Fan, C. (2025). An innovative humidity Enhancement-RC-mapping model with tailored identification framework for building HVAC demand response applications. Energy, 338, 138772. PDFDOI

[J20] Li, Q., Fan, C., Xu, L., Luo, X., & Hu, M. (2025). Multi-modal ensemble deep learning model for microclimate prediction using urban morphological maps. Energy, 337, 138594. PDFDOI

[J19] Wang, H., Hua, W., Peng, J., & Hu, M. (2025). Public sentiment analysis of data center energy consumption using social media data and large language models. Energy and Buildings, 341, 115802. PDFDOICode

[J18] Liu, W., Mao, H., Tian, Z., Luo, Y., Ma, L., Chen, X., Hu, M., Li, J., & Fan, J. (2025). Challenges of large-scale facade PV systems in dense urban environments in China. The Innovation Energy, 2, 100091. PDFDOI

[J17] Le Dréau, J., Lopes, R. A., O'Connell, S., Finn, D., Hu, M., et al. (2023). Developing energy flexibility in clusters of buildings - a critical analysis of barriers from planning to operation. Energy and Buildings, 300, 113608. PDFDOI

[J16] Luo, Z., Peng, J., Hu, M., Liao, W., & Fang, Y. (2023). Multi-objective optimal dispatch of household flexible loads based on their real-life operating characteristics and energy-related occupant behavior. Building Simulation, 16, 2005–2025. PDFDOI

[J15] Hu, M., Rajagopal, R., & de Chalendar, J. A. (2023). Empirical Exploration of Zone-by-zone Energy Flexibility: a Non-intrusive Load Disaggregation Approach for Commercial Buildings. Energy and Buildings, 296, 113339. PDFDOI

[J14] Hu, M., Stephen, B., Browell, J., Haben, S., & Wallom, D. C. H. (2023). Impacts of building load dispersion level on its load forecasting accuracy: Data or algorithms? Importance of reliability and interpretability in machine learning. Energy and Buildings, 285, 112896. PDFDOI

[J13] Luo, Z., Peng, J., Tan, Y., Yin, R., Zou, B., Hu, M., & Yan, J. (2023). A novel forecast-based operation strategy for residential PV-battery-flexible loads systems considering the flexibility of battery and loads. Energy Conversion and Management, 278, 116705. PDFDOI

[J12] Jiang, Z., Peng, J., Yin, R., Hu, M., Cao, J., & Zou, B. (2022). Stochastic modelling of flexible load characteristics of split-type air conditioners using grey-box modelling and random forest method. Energy and Buildings, 273, 112370. PDFDOI

[J11] Xu, L., Hu, M., & Fan, C. (2022). Probabilistic electrical load forecasting for buildings using Bayesian deep neural networks. Journal of Building Engineering, 46, 103853. PDFDOI

[J10] Hu, M., Ge, D., Telford, R., Stephen, B., & Wallom, D. C. H. (2021). Classification and characterization of intra-day load curves of PV and non-PV households using interpretable feature extraction and feature-based clustering. Sustainable Cities and Society, 75, 103380. PDFDOICode

[J9] Li, A., Xiao, F., Fan, C., & Hu, M. (2021). Development of an ANN-based building energy model for information-poor buildings using transfer learning. Building Simulation, 14, 89–101. PDFDOI

[J8] Hu, M., Xiao, F., & Wang, S. (2021). Neighborhood-level coordination and negotiation techniques for managing demand-side flexibility in residential microgrids. Renewable and Sustainable Energy Reviews, 135, 110248. PDFDOI

[J7] Hu, M., & Xiao, F. (2020). Quantifying uncertainty in the aggregate energy flexibility of high-rise residential building clusters considering stochastic occupancy and occupant behavior. Energy, 194, 116838. PDFDOI

[J6] Hu, M., Xiao, F., & Cheung, H. (2020). Identification of simplified energy performance models of variable-speed air conditioners using likelihood ratio test method. Science and Technology for the Built Environment, 26, 75–88. PDFDOI

[J5] Hu, M., Xiao, F., Jørgensen, J. B., & Wang, S. (2019). Frequency control of air conditioners in response to real-time dynamic electricity prices in smart grids. Applied Energy, 242, 92–106. PDFDOI

[J4] Hu, M., Xiao, F., Jørgensen, J. B., & Li, R. (2019). Price-responsive model predictive control of floor heating systems for demand response using building thermal mass. Applied Thermal Engineering, 153, 316–329. PDFDOI

[J3] Shan, K., Wang, J., Hu, M., & Gao, D.-c. (2019). A model-based control strategy to recover cooling energy from thermal mass in commercial buildings. Energy, 172, 958–967. PDFDOI

[J2] Hu, M., & Xiao, F. (2018). Price-responsive model-based optimal demand response control of inverter air conditioners using genetic algorithm. Applied Energy, 219, 151–164. PDFDOI

[J1] Hu, M., Xiao, F., & Wang, L. (2017). Investigation of demand response potentials of residential air conditioners in smart grids using grey-box room thermal model. Applied Energy, 207, 324–335. PDFDOI

[C9] Li, Q., Luo, X., & Hu, M. (2025). Urban Spatial Microclimate Prediction with Morphological Map-Based Ensemble Deep Learning Method. In Proceedings of Building Simulation 2025: 19th Conference of IBPSA. PDFDOI

[C8] Jie, P., Hu, M., Tian, S., Du, S., & Shi, X. (2025). High-resolution downscaling simulation of urban wind-thermal environments: An interpretable machine learning analysis of urban morphology. In Proceedings of Building Simulation 2025: 19th Conference of IBPSA. PDFDOI

[C7] Zhang, C., Hu, M., & Zhang, T. (2025). Deep Learning-Based Surrogate Modelling for Optimal Control of Climate-Responsive Adaptive Facade Systems. In Proceedings of Building Simulation 2025: 19th Conference of IBPSA. PDFDOI

[C6] Hu, M., Benson, S., & de Chalendar, J. A. (2024). Identifying Suitable Thermal Response Models for Demand Response Management in Multi-Zone Commercial Buildings. In Proceedings of ASim Conference 2024: 5th Asia Conference of IBPSA. PDFDOI

[C5] Gueguen, E., Wallom, D., & Hu, M. (2022). Renewable microgrids covering the heat and electricity needs of industrial parks. In European Council for the Energy Efficient Economy. PDFURL

[C4] Wang, L., Xiao, F., Cui, B., Hu, M., & Lu, T. (2019). Performance analysis of absorption thermal energy storage for distributed energy systems. Energy Procedia, 158, 3152–3157. PDFDOI

[C3] Hu, M., & Xiao, F. (2018). Model Predictive Control of Inverter Air Conditioners Responding to Real-Time Electricity Prices in Smart Grids. In 5th International High Performance Buildings Conference. PDFURL

[C2] Hu, M., & Xiao, F. (2017). Model-based optimal load control of inverter-driven air conditioners responding to dynamic electricity pricing. Energy Procedia, 142, 1953–1959. PDFDOI

[C1] Hu, M., & Xiao, F. (2017). Investigation of the Demand Response Potentials of Residential Air Conditioners Using Grey-box Room Thermal Model. Energy Procedia, 105, 2759–2765. PDFDOI