Presented the preliminary results of Urban Energy Modeling at the UF – City of Gainesville Research Awards Showcase held on October 9, 2018.
Aim and Approach
Cities are facing unprecedented growth with an increase in population and urbanization. The United Nations estimates that the global population will increase to 9.3 billion by 2050, which is an increase of 30% compared to the population in 2011. As development in dense urban areas continues, the scientific community must continue to observe, analyze, and interpret the effects of dense urbanization, including climate change impacts on urban sustainability, particularly buildings. The challenge is to test the feasibility of implementing green building technologies on a city-wide scale for energy policy decision-making. In this report, we discuss a novel physics-based approach to Urban Energy Modeling (UEM) using the City of Gainesville, Florida, USA as a case study. This city is the fourth largest city in Florida with a population of over 125,000. Our physics-based UEM approach can be used to virtually test the feasibility of implementing green building technologies on a city-wide scale for energy policy decision-making. Such a dynamic tool can be used by utility providers to accurately predict the demand of these communities in the future and mitigate risk.
Scientific Innovation and Relevance
Our Urban Energy Modeling (UEM) methodology to study the impact on the City of Gainesville residential building owing to climate change follows a four-step process – (1) Module 1 – Residential building input data creation, (2) Module 2 – Automated EnergyPlus™ input data file creation, (3) Module 3 – Energy simulation in distributed computing network, and (4) Module 4 – Model calibration and forecasting energy use owing to climate change. Each of the modules is discussed in detail in the following sub-sections. The City of Gainesville, FL, comprises of over 40,000 residential buildings. Data related to construction type, building system efficiencies, etc., were obtained from open-source county appraiser website. Extensive data cleaning and preparation was completed using ArcGIS. The data for the building footprint were obtained as GIS files for each property in the city. Several algorithms were developed to extract data to seamlessly create EneryPlus™ input files (.IDF) using python script. Data related to thermo-physical properties were automatically populated in the IDF files based on when the building was built complying with Florida Building Code – Residential. To reduce the overall time for simulation, we custom-built software tool to execute all 40,000+ EnergyPlus models. Essentially, we ran multiple instances of EnergyPlus on multiple cores to reduce the overall time for simulation. The calibrated results were incorporated into DSIM workbench, which allows seamless analysis across the neighborhood and building levels.
Preliminary Results and Conclusions
Our approach to UEM will help in effective decision-making and policy revisions for built environment regulations such as (a) estimating future energy demand due to population growth, climate change, etc.; (b) implementation of local regulations such as LED light, double pane windows etc., and its effect on the grid; (c) finding optimal standards of construction of future building such as heat transfer coefficient of walls, roof, etc.; (d) helping in understanding of how to balance the energy mix in the future as the city integrates different renewable energy technologies which are extremely seasonal; and (e) achieving an innovative strategy for investing in green and energy efficient technologies and assess the best Return of Investments (ROIs) of green technologies.
Project Team: Principal Investigator: Ravi Srinivasan; Students: Baalaganapathy Manohar, Rahul Aggarwal, Akshay Padwal, Nikhil Asok Kumar, and Vahid Daneshmand. Collaborators: Saranya Gunasingh, Scott Schuetter, Doug Ahl (SeventhWave)
Congratulatory letter from Congressman: