About Us +
Researchers in the Building Technology & Urban Systems Division (BTUS) at Lawrence Berkeley National Laboratory develop data and technologies that increase energy efficiency and improve the health, safety and comfort of building occupants, in the United States and worldwide.

We work closely with industry partners, academics and government officials to achieve these goals, and share our research widely
Research +
We are at the forefront of cutting-edge research that redefines building technology and explores all areas of urban systems.

We have been leaders for decades in developing energy-efficient windows, improving indoor air quality, coming up with new ideas to fix the nation's electricity grid, and so much more.

Visit our research areas at the right to find out more.
Colum 1 +
Colum 2 +
Publications +
Enjoy presentations from Building Technology & Urban systems research experts on a wide variety of topics in the areas of building energy efficiency, the electricity grid and how it relates to buildings and much more.
- Presentations
News
Tools & Guides +
Explore our tools, guidebooks and software and download for free.

We offer a variety of technologies designed to simulate and model real-world circumstances to assist in energy-saving programs and help building owners build better buildings. These tools can help calculate performance of building systems like windows and shades, help consumers and builders pick the best windows for a variety of applications and much more.

Publications

Publications By Research Area

2019

Wang, Wei, Tianzhen Hong, Xiaodong Xu, Jiayu Chen, Ziang Liu, and Ning Xu."Forecasting district-scale energy dynamics through integrating building network and long short-term memory learning algorithm."Applied Energy 248 (2019) 217 - 230. DOI

Xu, Xiaodong, Yifan Wu, Wei Wang, Tianzhen Hong, and Ning Xu."Performance-driven optimization of urban open space configuration in the cold-winter and hot-summer region of China."Building Simulation 12.3 (2019) 411 - 424. DOI

Wang, Wei, Tianzhen Hong, Ning Xu, Xiaodong Xu, Jiayu Chen, and Xiaofang Shan."Cross-source sensing data fusion for building occupancy prediction with adaptive lasso feature filtering."Building and Environment 162 (2019) 106280. DOI

Xu, Xiaodong, Chenhuan Yin, Wei Wang, Ning Xu, Tianzhen Hong, and Qi Li."Revealing Urban Morphology and Outdoor Comfort through Genetic Algorithm-Driven Urban Block Design in Dry and Hot Regions of China."Sustainability 11.13 (2019) 3683. DOI