The Nation’s transition towards renewable energy is creating the need for homes to vary their energy use across the hours of the day, and become responsive to the dynamic supply of renewable sources. Time-of-use rate structures have been developed by utilities and energy stakeholders as a strategy to incent home occupants to adjust their energy use patterns with supply. Nationally, approximately half of investor-owned-utilities utilize time-of-use rate structures. Carbon emissions intensity of electrical use varies throughout the day, providing further impetus to shift loads to off-peak hours, or when renewable sources make up a greater proportion of supply. Overall home energy performance can now be viewed as a combination of savings and flexibility.
Ambient Trends was selected and awarded grant funding by DOE’s Building Technologies Office to develop a Time-of-Use capability for their Home Energy Score™ platform. In cooperation with DOE’s National Renewable Energy Laboratory, Lawrence-Berkeley National Laboratory and Pacific Northwest National Laboratory, our team developed a computationally efficient methodology to use the Home Energy Score™ platform to analyze the impacts of time-of-use rates and the energy efficiency improvements affected by these time-relevant factors.
This new analytical capability utilizing existing data from the Home Energy Score™ platform serves as a digital twin for America’s housing stock with inference capabilities to better understand and model a multitude of energy generation, distribution, consumption, and efficiency program scenarios. This enables further optimization of utility rate structures, combination with demographic data via GIS to analyze and formulate solutions to equity and energy poverty concerns, and examine how extreme weather events affect electrical grids on a granular level to complement NREL’s tools for grid-scale digital twinning. The project will better aid homeowners, utilities, jurisdictions and government in analyzing housing and effective improvement measures as well as time-of-use-accurate calculation of forecast and actual carbon emissions.
The integration will enable live user interaction and evaluation of multiple scenarios using time-of-use data analytics, expanding the Home Energy Score™ tool’s user base and improving its accuracy for the growing proportion of time-of-use rate structures in the US.