Campus Units

Geological and Atmospheric Sciences, Civil, Construction and Environmental Engineering, Mechanical Engineering

Document Type

Conference Proceeding

Publication Version

Published Version

Publication Date

6-1-2019

Journal or Book Title

Canadian Society of Civil Engineers Annual Conference

Conference Title

Canadian Society of Civil Engineers Annual Conference

Conference Date

June 12-15, 2019

City

Montreal, Canada

Abstract

The energy consumption of buildings at the city scale is highly influenced by the weather conditions where the buildings are located. Thus, having appropriate weather data is important for improving the accuracy of prediction of city-level energy consumption and demand. Typically, local weather station data from the nearest airport or military base is used as input into building energy models. However, the weather data at these locations often differs from the local weather conditions experienced by an urban building, particularly considering most ground-based weather stations are located far from many urban areas. The use of the Weather Research and Forecasting Model (WRF) coupled with an Urban Canopy Model (UCM) provides means to predict more localized variations in weather conditions. However, despite advances made in climate modeling, systematic differences in ground-based observations and model results are observed in these simulations. In this study, a comparison between WRF-UCM model results and data from 40 ground-based weather station in Austin, TX is conducted to assess existing systematic differences. Model validations was conducted through an iterative process in which input parameters were adjusted to obtain to best possible fit to the measured data. To account for the remaining systemic error, a statistical approach with spatial and temporal bias correction is implemented. This method improves the quality of the WRF-UCM model results by identifying the statistic properties of the systematic error and applying several bias correction techniques.

Comments

This proceeding is published as Jahani, Elham, Soham Vanage, David Jahn, William Gallus, and Kristin S. Cetin. "City-scale energy modeling to assess impacts of extreme heat on electricity consumption and production using WRF-UCM modeling with bias correction." In Canadian Society of Civil Engineers Annual Conference. 2019. Posted with permission.

Copyright Owner

Canadian Society for Civil Engineering

Language

en

File Format

application/pdf

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Article Location

 
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