Technology Description

Energy information systems have become a cost‐effective measure to reduce energy consumption of buildings. However, current generation EIS are limited to the use of historical data and therefore cannot be used to conduct fault detection and diagnostics or to conduct scenario analyses for more efficient operational strategies. This demonstration will augment the EIS in use at the Naval District Washington (NDW) with fault detection, diagnostics, and optimization methods. To further support NDW operational and energy management staff, the EIS will also be integrated with geospatial, localized sensor data from the installation's Smart Grid Pilot project. The approach is based on Bayesian statistical methods that use calibrated physics‐based models. The fault detection and diagnostics portion will complement the optimization, in part by preventing component‐level degradation and errors in the execution of otherwise efficient operational strategies. System output will be recommendations to the site operator on how to prioritize equipment repairs, identify malfunctioning controls, and suggest improvements to building operation. Close collaboration between the building facility manager, researchers at LBNL, and an EIS provider, EnergyICT, will help address the needs of the facility operator and provide a path to scale the technology to other sites.