Method and system for heating auto-setback
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Solution Overview
Problem
Conventional HVAC systems lack the ability to autonomously determine optimal operating parameters when a space is unoccupied, leading to unnecessary energy consumption as they rely on user-inputted set-point temperatures without adjusting for occupancy status.
Innovation Solution
An intelligent HVAC controller predicts temperature changes during unoccupied times and adjusts operation accordingly, determining if the predicted temperature is below the set-point, and if so, operates the system to reach the set-point before the space is occupied, thereby optimizing runtime without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If the HVAC system operates continuously to maintain set-point temperature, then the temperature comfort is improved, but energy consumption increases
Solution Approach 1:
The system performs preliminary heating or cooling during unoccupied periods to ensure the space reaches the desired set-point temperature before occupancy is expected to resume. The controller predicts temperature changes and schedules HVAC operation in advance, so the space is comfortable when needed without requiring continuous operation.
Solution Approach 2:
The system uses occupancy detection and temperature prediction algorithms to autonomously determine when HVAC operation is necessary. The controller self-adjusts the set-point temperature and runtime based on predicted occupancy patterns and thermal dynamics, eliminating the need for continuous operation while maintaining comfort.
2Use of energy by moving object
If the HVAC system shuts off during unoccupied time to save energy, then energy consumption is reduced, but temperature control capability deteriorates
Solution Approach 1:
The system incorporates temperature prediction based on thermal models and occupancy detection as feedback mechanisms. The controller continuously monitors space conditions, predicts future temperature trends, and adjusts HVAC operation accordingly. This feedback loop ensures energy-saving shutdowns during unoccupied periods while automatically restoring temperature control before occupancy resumes.
Solution Approach 2:
The system dynamically adjusts the set-point temperature and HVAC runtime based on real-time occupancy status and predicted temperature changes. During unoccupied periods, the set-point may be relaxed to save energy, but the controller dynamically recalculates and restores appropriate temperature control as occupancy is detected or predicted, making the system adaptable rather than static.
3Device complexity
If simple thermostat with user-input set-point is used, then device complexity is reduced, but adaptability to occupancy status deteriorates
Solution Approach 1:
The system enables the thermostat to autonomously determine optimal set-point temperatures based on detected occupancy status and predicted temperature changes. Instead of requiring continuous user input or complex programming, the thermostat self-adjusts operating parameters by detecting whether the space is occupied or unoccupied and automatically scheduling HVAC operation to maintain comfort only when necessary.
Data Source
AI summary
A method of operating an HVAC system using a controller includes predicting a first predicted temperature of an enclosed space during an unoccupied time with the HVAC system off. The controller determines if the first predicted temperature is less than a set-point temperature. Responsive to a determination that the first predicted temperature is less than the set-point temperature, the controller predicts a second predicted temperature of the enclosed space if the HVAC system is operated for a first runtime. The controller determines if the second predicted temperature is less than the set-point temperature and, responsive to a determination that the second predicted temperature is not less than the set-point temperature, the controller operates the HVAC system for the first runtime.