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 a key strategy for cities to reduce green-house-gas emissions and mitigate climate change. Planning and evaluating retrofit strategies for buildings requires a deep understanding of the physical characteristics, operating patterns, and energy use of the building stock. This is a challenge for city managers as data and tools are limited and disparate.
City Building Energy Saver (CityBES) is a web-based data and computing platform, focusing on energy modeling and analysis of a city's building stock to support district or city-scale efficiency programs. CityBES uses an international open data standard, CityGML, to represent and exchange 3D city models. CityBES employs EnergyPlus to simulate building energy use and savings from energy efficient retrofits. CityBES provides a suite of features for urban planners, city energy managers, building owners, utilities, energy consultants and researchers.
The following figure shows the three layers of the software architecture of CityBES: the Data layer, the Algorithms and Software layer, and the Use Cases layer. The Data layer includes the weather data, and the CityGML 3D city model. The Software layer includes EnergyPlus, OpenStudio and CityBES. The Use Cases layer provides examples of potential applications, including energy benchmarking, urban energy planning, energy retrofit analysis, building operation improvement, as well as performance visualization.
CityBES also generates load profiles for buildings in an urban district, using the USDOE Commercial Prototype Building Models and the and the Commercial Reference Buildings. The load profiles include cooling loads, heating loads, domestic hot water loads, and electrical loads for fans and pumps. The load profiles can be used in sizing and simulation of performance of district heating and cooling systems.
Y. Chen, T. Hong. Impacts of Building Geometry Modeling Methods on the Simulation Results of Urban Building Energy Models. Applied Energy, 2018, 215:717-735, DOI: 10.1016/j.apenergy.2018.02.073.
Y. Chen, T. Hong, M.A. Piette (2017). Automatic generation and simulation of urban building energy models based on city datasets for city-scale building retrofit analysis. Applied Energy, 205: 323-335. DOI:10.1016/j.apenergy.2017.07.128
CityBES: A Web-based Platform to Support City-Scale Building Energy Efficiency. Urban Computing 2016. PDF
City-Scale Building Retrofit Analysis: A Case Study using CityBES. Building Simulation 2017. PDF
CityBES is sponsored by Lawrence Berkeley National Lab, under the Laboratory Directed Research and Development ( LDRD ) Program.