2017 ASHRAE Annual Conference

National labs, universities, and industry are all developing significant capabilities for urban-scale building energy modeling…once a virtual city is constructed. To construct the models, most rely on local data sources that work at the scale of a city or county (such as a tax assessor’s database) or flyover of the area of interest, but do not use data sources or algorithms that would scale to areas the size of a metropolis, state, or entire country. This presentation will show recent advances in scalable capabilities for automatically creating fully-articulated OpenStudio and EnergyPlus models of individual buildings for any area of interest.

A building’s façade is a major element that accounts for 70% of building energy performance. Compared with the internal mechanical system and operation schedule, façade features information is relatively easy to obtain from the visual aspects of a building. Instead of using traditional and complicated simulation methods, a mathematical model can be established to estimate EUI baselines based on sufficient existing building practices data. This prediction modeling approach will provide a more realistic EUI estimation tool for calculating an energy use baseline and will enable real-time energy usage monitoring and management of each targeted building.

Buildings in cities consume 30 to 70% of the cities’ total primary energy. Retrofitting the existing building stock to improve energy efficiency and reduce energy use is necessary to reduce green-house-gas emissions and mitigate climate change. We present a case study on district-scale energy retrofit analysis using CityBES, a web-based toolkit developed by LBNL. Two retrofit scenarios are studied: evaluating energy savings and cost of typical energy conservation measures (ECMs) for a portfolio of hundreds of buildings in downtown San Francisco; and optimizing a package of ECMs that can achieve 50% energy savings for all buildings in the district.