Optimized Commercial Control Technology Of Plug-loads & Lighting (OCCTOPI)
Integrating plug load and lighting controls in commercial buildings
The Regents of the University of California, on behalf of the San Diego campus
Recipient
La Jolla, CA
Recipient Location
38th
Senate District
77th
Assembly District
Active
Project Status
Project Update
The project started with an audit of lighting and plug loads at our two field demonstration sites. Electrical meter data was also recorded which was used to develop a load profiler algorithm that provides building managers with insights into when their buildings use electricity and where opportunities for savings may be. The project team also set up a laboratory testbed to evaluate hardware and prototype software features. Early versions of our software for occupancy estimation and forecasting as well as for advanced plug load control have been developed. The first version of our BACnet driver for Home Assistant is also nearing completion.
The Issue
Plug loads are plug-in electric loads and they account for an increasingly significant percentage of building energy consumption. In 2018, plug loads accounted for twenty-seven percent (27%) of California's commercial electricity consumption. Most plug loads are left on 24/7 and lack power management features. Even if plug loads have energy savings settings, those settings often have not been set up or are disabled. Integrating plug load control with lighting systems enables advanced energy management strategies that leverage occupancy data provided by passive infrared sensors often used in lighting systems. In addition to reducing energy consumption and operating costs, this energy management can play an important role for building electrification to reduce peak loads and to stay within capacity limits.
Project Innovation
Optimized Commercial Control Technology Of Plug-loads & Lighting (OCCTOPI) is an open-source software for affordably integrating plug load and lighting controls in commercial buildings. OCCTOPI unlocks the potential of flexible plug and lighting loads by providing intelligent energy management functions such as peak load reduction and demand response programs. Occupancy sensors and smart wall switches will make the existing simple lighting system connected and enable communication with the plug load controllers. The systems will be managed using a Home Assistant (HA)-based control platform connected to the building electric meter to save energy from both systems. OCCTOPI provides greater value to the occupant experience by offering scenes and automations that complement and enhance the occupant workflow.
Project Goals
Project Benefits
The project utilizes an existing, open-source home automation platform that will be augmented with new software features to make it suitable for commercial applications, such as BACnet support. This approach takes advantage of existing device integrations to make affordable, off-the-shelf consumer products available for commercial use. Both residential and commercial users will benefit from the novel algorithms developed in the project for energy analytics, occupancy estimation and forecasting, and occupancy-based controls for plug loads.
Affordability
Annual energy savings translate to lower energy cost to ratepayers. The ability to manage their PL energy usage, allows ratepayers to strategically adjust PL consumption given time of use (TOU) rates.
Reliability
Reducing peak energy usage by PLC can help ratepayers during demand response events and CAISO Flex Alerts. Aggressively turning off PL can prevent rolling blackouts during times of grid stress. Being able to shut off a large fraction of unused PL can significantly contribute to reducing peak energy usage.
Key Project Members
Keaton Chia
Jan Kleissl
Felix Villanueva
Subrecipients
