The Department of Defense (DoD)has one of the largest real estate portfolios in the world. As the DoD seeks to modernize its control and monitoring systems, highly scalable deployment solutions are paramount to achieving energy efficiency and performance management goals. 

The objective of this project is to showcase the benefits of standardized building semantic models through a control performance assessment (CPA) use case in real-world applications and serve as a pilot for the semantic model standards and guidelines that are being developed for the DoD in a separate ongoing ESTCP project (EW21-5129). The project will deploy semantic models in two existing DoD environments—U.S. Army Reserve (USAR), and U.S. Air Force—highlighting their transferability and scalability benefits across the DoD. Implementing those newly developed frameworks in the real-world systems of multiple DoD services will provide valuable real-world validation and feedback. The project will also serve as a roadmap for installations across the DoD to implement semantic models in a way that adheres to those standards and guidelines. This project will quantify the labor and time required to deploy an advanced analytic application using standardized semantic models, as compared to current methods.

A semantic building model is a digital representation of a building and its systems that uses a structured and consistent method for capturing the meaning of and relationships between data points in the building and connected control systems. The current state-of-practice for capturing this metadata is an ad hoc combination of naming conventions and bespoke mappings. Several standards for semantic models exist today.  

Foundational investigations conducted in the ongoing ESTCP project will be leveraged to identify the most suitable standard for the DoD. ControlScore is a scalable CPA technology that provides a way to assess building control performance without the need for a controls expert manually sifting through data. ControlScore produces a single metric that can be tracked to evaluate building performance. It has been successfully piloted in USAR, Pacific Northwest National Laboratory, and U.S. General Services Administration buildings, with case studies highlighting both the benefits of a standardized CPA method across large portfolios, and deployment challenges associated with a lack of consistent and well-defined metadata. Semantic models enable faster and wider deployment of ControlScore and similar applications for the DoD.

Approximately 30% of the DoD’s energy use is attributed to buildings and their connected systems, with much of that energy lost to inefficient operation. ControlScore will save money and energy in DoD buildings by quickly identifying where systems are performing poorly without requiring the time and expertise that building CPA typically involves. While semantic models and CPA do not, by themselves, save energy, they are critical enablers for saving energy at scale. Ultimately, the project will inform DoD decision-makers interested in modernizing and transitioning building control systems to cloud-based systems that support a variety of vendors and technologies in a common environment. (Anticipated Project Completion - 2028)