Impacts of building geometry modeling methods on the simulation results of urban building energy models

Abstract

Urban-scale building energy modeling (UBEM)-using building modeling to understand how a group of buildings will perform together-is attracting increasing attention in the energy modeling field. Unlike modeling a single building, which will use detailed information, UBEM generally uses existing building stock data consisting of high-level building information. This study evaluated the impacts of three zoning methods and the use of floor multipliers on the simulated energy use of 940 office and retail buildings in three climate zones using City Building Energy Saver. The first zoning method, OneZone, creates one thermal zone per floor using the target building's footprint. The second zoning method, AutoZone, splits the building's footprint into perimeter and core zones. A novel, pixel-based automatic zoning algorithm is developed for the AutoZone method. The third zoning method, Prototype, uses the U.S. Department of Energy's reference building prototype shapes. Results show that simulated source energy use of buildings with the floor multiplier are marginally higher by up to 2.6% than those modeling each floor explicitly, which take two to three times longer to run. Compared with the AutoZone method, the OneZone method results in decreased thermal loads and less equipment capacities: 15.2% smaller fan capacity, 11.1% 1 smaller cooling capacity, 11.0% smaller heating capacity, 16.9% less heating loads, and 7.5% less cooling loads. Source energy use differences range from-7.6% to 5.1%. When comparing the Prototype method with the AutoZone method, source energy use differences range from-12.1% to 19.0%, and larger ranges of differences are found for the thermal loads and equipment capacities. This study demonstrated that zoning methods have a significant impact on the simulated energy use of UBEM. One recommendation resulting from this study is to use the AutoZone method with floor multiplier to obtain accurate results while balancing the simulation run time for UBEM.

Analysis of Energy Saving Effect and Cost Efficiency of ECMs to Upgrade the Building Energy Code

“…The ECM database includes a description of investment cost and performance value for each ECM. The users can select feasible individual ECM or ECM packages based on energy savings, energy costs reduction, and PP [16]. The Opt-E-Plus [17], an energy performance optimization program for commercial buildings, has a feature that can identify the most economic ECMs by automatically performing repeated simulations.…”

A review on occupant behavior in urban building energy models

“…The City Building Energy Saver (CityBES) by Hong et al [89] is a tool for retrofit analysis of small and mediumsized office and retail buildings. Chen et al [88,87,96] present case studies using CityBES in downtown San Francisco. EnergyPlus models are created from data on building footprint, age, type, gross floor area, and number of stories, using the Commercial Building Energy Saver Toolkit (CBES) [97].…”

An Analysis of the Effectiveness of Greenhouse Gas Reduction Policy for Office Building Design in South Korea

“…Li et al [33] developed a reference building to examine the refurbishment of low-carbon, high-rise residential buildings in Hong Kong, a city with a subtropical climate, and reviewed 88 options. Although reference models have also been used to evaluate the energy consumption of residential buildings [34,35], they can additionally be applied to evaluate the energy consumption during the lifecycle of buildings [36], as well as for analyzing the geometry of energy models for urban buildings and cities, in general [37][38][39]. Reference buildings can also be used to inform the inspection and understanding of low-energy, low-carbon building technology in residential and non-residential buildings.…”