Smart Ventilation for Advanced California Homes
Optimizing indoor air quality, energy efficiency, and comfort with smart ventilation
Lawrence Berkeley National Laboratory
Recipient
Berkeley, CA
Recipient Location
9th
Senate District
14th
Assembly District
$1,500,000
Amount Spent
Completed
Project Status
Project Result
The team completed development of an integrated energy simulation model that enables quantitative evaluation of the energy demand, energy cost (based on time-of-use pricing), and air quality implications of various smart ventilation strategies. The team also developed a range of optimized control algorithms for various home ventilation scenarios. The final report was published in July 2020. Prior to publication of the final report, the team completed several journal publications based on literature review and development of guidelines for indoor air quality (IAQ) metrics. Metrics have been used in a U.S. Department of Energy project to support development of a home IAQ scoring system.
The Issue
As California advances zero net energy homes, heating and cooling loads shrink but the need to safeguard indoor air quality remains unchanged. Current approaches to ventilation would result in ventilation contributing a larger fractional load. In addition, current approaches that specify ventilation per hour are not responsive to occupancy or to concentrations of health-damaging air pollutants. Smart ventilation, which involves varying ventilation in response to temperature, occupancy, air pollutant concentrations, may improve indoor air quality while reducing energy demand. Smart ventilation could also help offset demand during peak periods by shifting ventilation loads to off-peak hours.
Project Innovation
This study explored how real-time monitoring and automatic controls can be used in home ventilation systems to improve energy efficiency and/or optimize consumption for time-of-day load balancing. Specifically, the study considered optimization of ventilation for indoor air quality for zones (i.e., air quality in different rooms within buildings). The study used computational simulations leveraging multiple well-established platforms to develop and evaluate control schemes for home ventilation systems. Key evaluation criteria were the modeled ventilation-related energy used over a year of operation, and the indoor air quality relative to a minimally code-compliant continuously operating ventilation system.
Project Goals
Project Benefits
This work built on efforts of the past decade that have facilitated dynamic ventilation approaches. The project used simulation approaches to determine how energy, indoor air quality (IAQ), peak period demand, and comfort can be optimized using smart ventilation. The results from the project will help smart home automation service providers and their consumers identify effective smart ventilation strategies and provide important, as well as provide information that the Energy Commission could potentially use in the development of future ventilation standards.

Affordability
The project has the potential to result in reduced electricity consumption and/or peak shifting by developing smart ventilation strategies to optimize system performance.
Key Project Members

Max Sherman

Iain Walker

Brennan Less
Subrecipients

Saturn Resource Management

Aereco S.A.

Match Partners

Lawrence Berkeley National Laboratory

United States Department of Energy

Aereco S.A.
