Customer-controlled, Price-mediated, Automated Demand Response for Commercial Buildings
Creating a virtual building management system to provide large and small commercial customers with choices for DR capability.
The Regents of the University of California (CIEE)
Recipient
Berkeley, CA
Recipient Location
9th
Senate District
14th
Assembly District
$3,993,312
Amount Spent
Completed
Project Status
Project Result
The project is complete. The researchers successfully developed a cost-effective energy management system that allowed a wide range of service offerings as well as effective and automated price-based management. This is achieved by developing automated control systems capable of responding to dynamic pricing and program designs. Most buildings that installed networked thermostats showed modest savings of 7-9%. DR event testing across 13 buildings resulted in an average of daily savings of $5.53, and 21 kWh in energy savings, with as high as $31.68 and122.01 kWh. The near-term target market is research groups who need data for analytics. The mid-term target market are utility program designers and startup companies who need building and system data. The platform will continue to be used in additional research projects funded by NYSERDA and DOE.
The Issue
The services demanded by commercial building customers--heating, cooling, ventilation, lighting, and so on--require significant energy and contribute to peak energy demand. Large commercial customers typically have a building management systems (BMS) that can be used to control HVAC and lighting in order to respond to price signals. However, small commercial customers typically do not have such capability, and thus cannot easily participate in demand response (DR). There are few DR solutions that address the complexity and heterogeneity for the diverse and varying needs of all commercial customers.
Project Innovation
The purpose of this project is to improve small and large commercial customer participation in demand response programs by providing a cost-effective energy management system that allows a wide range of service offerings as well as effective and automated price-based management. The project will develop automated control systems capable of responding to dynamic pricing and program designs. Design improvements include: 1) receive price signals and evaluate energy demand; 2) enable heterogeneous customers to adapt to DR with individual preferences; 3) track, evaluate and control multiple devices; 4) interoperate with various building systems; 5) retain the electrical usage history of connected devices; 6) provide pricing based load management algorithms; 7) coordinate to maintain load diversity; 8) provide security; and 9) provide value by allowing customers to minimize the opportunity costs of participating by selecting the least-impactful load management strategy.
Project Benefits
This project developed an open source software solution that is combined with an open architecture enabling platform. The eXtensible Building Operating System (XBOS/DR) can interface with multiple hardware devices from different vendors as well as include software applications from various vendors. With its ability to create a virtual building management system for small commercial buildings by networking thermostats and other controllers, XBOS/DR can provide large and small commercial customers with a variety of choices for DR capability. The open architecture can foster technical innovation by third-party vendors and other manufacturers in providing energy services.
Affordability
The recipient estimates that the XBOS software has the potential to reduce energy costs for ratepayers by $260 million per year in 2024 - due to lower demand charges, increased electric grid energy efficiency, reduced energy end-use from persistent efficiency in parallel with DR, and lower generation costs.
Environmental Sustainability
The project has the potential to reduce 930,000 metric tons of CO2e and 130 metric tons of NOx emissions per year avoided in 2024 from: increased electric grid energy efficiency, increased end-use energy efficiency in parallel with demand-management, and an increased fraction of intermittent operationally GHG-free renewable electricity generation.
Reliability
The XBOS software has the potential to reduce or shift 450 MW of peak electric demand by 2024. This is a 150% increase beyond the current 293 MW of DR from a combination of nonevent-based programs, critical peak pricing, and peak-time rebates estimated by the California Energy Demand 2016-2026 Revised Forecast.
Key Project Members
Therese Peffer
Subrecipients
Quantum Energy Services & Technologies, Inc. (DBA: QuEST)
Siemens Corporation, Corporate Technology
Carnegie Mellon University, Silicon Valley
Match Partners
Quantum Energy Services &
Technologies, Inc. (DBA: QuEST)
Siemens Corporation, Corporate Technology
