Abstract

The methodology presented in this talk integrates building (facility) digital twin technology with asset condition data and business value to improve building energy efficiency and asset performance and reliability. The methodology takes advantage of both dynamic data, such as energy metered data of individual assets, asset condition and performance data, occupancy; and static data, such as, business objectives of the buildings, functional decomposition of the building and zoning, etc. Assets are (partially or fully) connected (with sensors and embedded devices) and their real time conditions are accessible at all times. Building digital twin runs in parallel to the actual physical building and proactively participates in Operations and Maintenance (O&M). The digital twin is expected to reside at a layer above the typical Building Energy Management System (BEMS) with planning time scaled in days or more, and operational time scaled in minutes, hours or longer. The technology can provide solutions to building owners and operators to proactively diagnose faults and failures, run what-if scenarios and benchmarking, optimize building O&M, and carry out planning and resource analysis. Within this framework a network or community of buildings can be modeled by connected and communicating digital twins in a hierarchical or distributed manner.