Machine to Machine (M2M) Technology in Demand Responsive Commercial Buildings

David S. Watson, Mary Ann Piette, Osman Sezgen, and Naoya Motegi, Lawrence Berkeley National Laboratory

Keywords

Abstract

Machine to Machine (M2M) is a term used to describe the technologies that enable computers, embedded processors, smart sensors, actuators and mobile devices to communicate with one another, take measurements and make decisions - often without human intervention. M2M technology was applied to five commercial buildings in a test. The goal was to reduce electric demand when a remote price signal rose above a predetermine price. In this system, a variable price signal was generated from a single source on the Internet and distributed using the meta-language, XML (eXtensive Mark-up Language). Each of five commercial building sites monitored the common price signal and automatically shed site-specific electric loads when the price increased above a predetermined threshold. Other than price signal scheduling, which was set up in advance by the project lead researchers, the system was designed to operate without human intervention during the two-week test period.

Although the buildings responded to the same price signal, each building used substantially different communication infrastructures. This study provides an overview of the technologies used at each building site, the price generator/server, and each link in between. Network architecture, security, data visualization and site-specific system features are characterized.

The results of the test are discussed, including: functionality at each site, measurement and verification techniques, and feedback from energy managers and building operators. Lessons learned from the test and potential implications for widespread rollout are provided.