Urban Scale Modeling & Climate Change
This work is funded by the National Science Foundation:
Collaborative Research: Climate Impacts on the Urban Built Environment (Grant No. 2035150)
Collaborative Research: Growing Convergence Research: Convergence Around the Circular Economy (Grant No. 1934824)
There is growing attention to urban building energy modeling; however, data scarcity and dependency on assumptions and secondary data are the identified challenges.
In addition, focusing on commercial buildings that have more complex properties and systems will enhance understanding of building energy use at urban scale.
The goal of this research is to propose a novel photogrammetry and image processing framework to retrieve essential envelope properties such as window to wall ratio, floor count, and wall materials to mitigate assumptions and secondary data.
Other goals of this research were validating the simulation results based on actual energy use data and employing the urban building energy model to assess impacts of energy conservation strategies on energy use of commercial buildings at urban scale. The results from the urban building energy model show that total energy use and energy use by different end uses correlate with the commercial building use types. The energy use intensity of the commercial building use types ranges from 74 and 1302 kWh/m2.
Moreover, variations in the total energy use of commercial buildings with the same use type are because of unique characteristics or properties of buildings like window to wall ratio, orientation, floor counts, and wall materials.
The average energy use intensity of the commercial buildings can be reduced between 2% and 10% by implementing low to medium cost energy conservation strategies: adjusting setpoint temperature, upgrading to LED lighting, and reducing plug and process loads.
Mohammadiziazi, R., Bilec, M.M.* (2022). “Building Material Stock Analysis Is Critical for Effective Circular Economy Strategies: A Comprehensive Review.” Environmental Research: Infrastructure and Sustainability. https://doi.org/10.1088/2634-4505/ac6d08.
Mohammadiziazi, R., Bilec, M.M.* (2021). “Integrating Climate Change with Urban Building Energy Modeling: Case of A Commercial Building Stock.” Proceedings of the 17th IBPSA Conference. https://doi.org/10.26868/25222708.2021.30869.
Mohammadiziazi, R., Copeland, S.+, Bilec, M.M.* (2021). “Urban building energy model: Database development, validation, and application for commercial building stock.” Energy and Buildings, 248:111175. https://doi.org/10.1016/j.enbuild.2021.111175
Mohammadiziazi, R., Bilec, M.M.* (2020). "Application of Machine Learning for Predicting Building Energy Use at Different Temporal and Spatial Resolution under Climate Change in USA." Buildings, 10 (8), 139. https://doi.org/10.3390/buildings10080139
Mohammadiziazi, R., Bilec, M.M.* (2019). "Developing a framework for urban building life cycle energy map with a focus on rapid visual inspection and image processing." Procedia CIRP, 80, 464-469. https://doi.org/10.1016/j.procir.2019.01.048