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HVAC Prediction for a Cost-Limited Home Thermostat

Detailed Technology Description

Background:  Most homeowners would like to spend less on their air-conditioning and heating bills during the extreme heat of summer, and extreme cool of winter. Trivially, homes can spend $0 on heating and cooling by fully disabling their temperature control units---however, this may lead to discomfort. On the other hand, arbitrarily selected comfort levels may result in high costs to the homeowner which are not discovered until the previous month's electricity bill arrives. What is nontrivial is the ability to plan to spend a fixed amount (or an amount within an accepted tolerance) on the temperature of a building each month.Invention: This technology addresses this problem by introducing a new cost-limited thermostat which provides real-time feedback on temperature-cost correlation and puts consumers in control of balancing their comfort and budget. When the temperature schedule or monthly budget is changed, the thermostat immediately displays how one affects the other allowing the user to always be in control of their thermostat and their budget.  Application: This product could one day be integrated into any homeowners HVAC unit, to allow them to accurately predict and control the costs of maintaining a thermostat at different temperatures. This application has the potential for not only homeowners, but large businesses and any building or structure using an HVAC system. Advantages: This invention has been demonstrated to be superior to the state-of-the-art in (a) theory, (b) simulations, and (c) using real data. Our simulation results show orders of magnitude in improvement, as compared to traditional methods. Real results from data closely replicate the performance of our simulations. proposed method accurately and immediately shows changes in cost as temperatures are changed; runs on embedded hardware and does not need any external toolbox; provides a link between setpoints, and a bounded estimate of cost at those setpoints; method uses setpoints based on cost, not temperature.  Lead Inventor: Jonathan Sprinkle UA ID:  UA12-122

*Abstract

None

*Principal Investigator

Name: Jonathan Sprinkle, Assistant Professor

Department: Electrical & Computer Engineering

Name: Susan Lysecky, Assistant Professor

Department: Electrical & Computer Engineering

Name: Xiao Qin, Graduate Research Assistant

Department: Electrical & Computer Engineering

Country/Region

USA