Technology Demonstration & Deployment

Technology Demonstration and Deployment

Energy management and information systems icon

Technology demonstration and validation projects identify and demonstrate cost-effective energy management technologies in commercial buildings.

The Smart Energy Analytics Campaign

The Smart Energy Analytics Campaign [smart-energy-analytics.org] encourages the use of a wide variety of commercially available Energy Management and Information Systems (EMIS) technologies and ongoing monitoring practices to help uncover energy-saving opportunities and improve building performance. Participants in Campaign receive technical assistance, peer group support and are eligible for national awards.

Better Buildings Alliance EMIS Project Team

Working with a the project team comprised of Better Building partners, commercial building owners, and service providers, Berkeley Lab researchers developed tools and resources [emis/better-buildings-alliance-emis-rd-team] to help address questions on the distinguishing factors and attributes of EMIS.

Chicago skyline at dusk

Field Validation of Building IQ Technology

Tested in a five building cohort, this study was a field validation and verification of the BuildingIQ's Predictive Energy Optimization (PEO) technology. PEO technology is describes as a software-as-a-service (SaaS) platform that optimizes commercial building HVAC control for system efficiency, occupant comfort, and cost.

Data-Driven and Physics Model-Based Tool for Energy Efficiency in Central Cooling Plants

In a field demonstration, Berkeley Lab researchers verify the feasibility of employing a model-based approach to central plant operation and diagnostics at U.S. Department of Defense facilities.

Protocol and Performance Data for Energy Management and Information Systems Technologies

Currently there is not yet a standardized state of the art protocol for the assessment of EMIS technologies, and validation studies are often conducted differently with disparate design and metrics, and are difficult to generalize. This ongoing work aims to develop standardized field validation protocols and datasets for EMIS software analytics technologies.