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University, NIST Researchers Develop Strategy for Cutting Home HVAC Electricity Costs

University, NIST Researchers Develop Strategy for Cutting Home HVAC Electricity Costs

To help reduce electricity consumption and its costs, university and NIST researchers proposed a strategy for controlling residential heating, ventilation, and air conditioning (HVAC), in Comparing Economic Benefits of HVAC Control Strategies in Grid-Interactive Residential Buildings, published in Energy and Buildings. The lead author, Brian Woo-Shem of Santa Clara University, was a 2021 recipient of a NIST Summer Undergraduate Research Fellowship (SURF).

This HVAC control strategy considers:

  • The range of comfortable indoor temperatures – or the “the adaptive comfort model”
  • Adjusting temperatures based on probability of occupants in the residence
  • Real-time energy prices which vary throughout the day
  • Optimizing the HVAC schedule to:
    • Reduce cost
    • Maintain thermal comfort
    • Respond to renewable energy availability

To validate this strategy, researchers developed a simulation framework; this involved a building energy simulation and advanced building controls simulations – all connected with NIST’s Universal CPS Environment for Federation (UCEF) co-simulation platform. Researchers used the resulting co-simulation to model this HVAC strategy applied to a single-family residence in Sacramento, CA during a typical summer week.

Results showed that the strategy’s emphasis on probability of occupancy, adaptive thermal comfort, and HVAC schedule optimization reduced costs by 50.1 %, electricity consumption by 52.9 %, and discomfort by 56.2 %, compared to just relying on thermostat settings. Results also suggested that energy consumption could be shifted away from peak times if:

  • The proposed HVAC control strategy is implemented across the grid
  • The strategy emphasizes occupancy probability and optimized HVAC scheduling
  • Demand-based pricing occurs

In the future, researchers seek to develop more diverse building, appliance, and occupancy models, and expand this simulation framework for use with multiple buildings.

Released June 1, 2023, Updated July 14, 2023