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

15th

Assembly District

beenhere

$1,500,000

Amount Spent

closed

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

Create indoor air quality controls to include contaminant exposure while minimizing energy use and reducing peak demand
Demonstrate that smart ventilation systems can provide acceptable indoor air quality in zero net energy homes.
Determine how best to design ventilation systems for California zero net energy homes.

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.

Lower Costs

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

Project Member

Max Sherman

Senior Staff Scientist
Iain Walker

Iain Walker

Scientist
Brennan Less

Brennan Less

Senior Scientific Engineering Associate
LBNL

Match Partners

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