A Risk-Based Framework for Dynamic Assessment and Prioritization of Flexible Building Loads

Lead Performer: Lawrence Berkeley National Laboratory – Berkeley, CA
Partners:
-- U.S. General Services Administration – Washington, DC
-- District of Columbia Office of Resilience – Washington, DC
-- Deloitte Consulting – Arlington, VA
-- Danfoss Group – Nordborg, Denmark
DOE Total Funding: $1,250,000
FY19 DOE Funding: $681,000
Project Term: October 1, 2018 – September 30, 2021
Funding Type: Lab Call

Project Objective

This project will develop an open-source decision tool for commercial building operators that dynamically ranks flexible load control options based on associated risks, benefits and operator preferences. The project team will adapt assessment methods that guide decisions in public health and emergency response to develop a robust and adaptable open-source tool for comparing the risks and benefits of flexible load adjustment options. The method will consider the time- and context-dependency of risk valuations and decision-maker load preferences. The project’s outcome addresses the need for energy management software that can guide broader participation in demand response (DR) programs in the commercial sector. Currently, commercial operators either lack the automated control resources needed to respond to DR signals on short time scales or rely on predetermined sets of actions that do not account for changes in operational patterns and control priorities, exposing operators to substantial risks of service losses (e.g., reduced occupant comfort, productivity).

Project Impact

The decision-making tool yielded by this project will facilitate broader and more effective demand-response participation in commercial buildings by removing the burden of manual flexible load prioritization from building operators while retaining their response preferences. The tool will allow for their preferences to be updated over time. The project’s outcome provides a quantitative basis for making dynamic adjustments to energy demand in response to changing grid conditions, a key capability targeted by the BTO Grid-Interactive Efficient Buildings (GEB) initiative.  

Contacts

DOE Technology Manager: Erika Gupta
Lead Performer: Jared Langevin, Lawrence Berkeley National Laboratory

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