Occupancy-Aware HVAC Preconditioning for Setback Temperature Recovery
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Solution Overview
Problem
Conventional hotel HVAC and water heating systems face inefficiencies due to inaccurate temperature setpoint recovery times and variable user occupancy, leading to energy wastage and equipment damage, as well as inadequate planning for heated water consumption based on projected user numbers.
Innovation Solution
A user location tracking system using mobile devices with transmitters and an application server to determine user arrival times, calculate occupancy levels, and adjust HVAC and water heating settings dynamically, optimizing energy usage and resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the setback temperature is set too far from the setpoint temperature for energy conservation, then energy savings are improved, but the temperature recovery time becomes excessively long and comfort is compromised
Solution Approach 1:
The system performs preliminary action by detecting user approach and pre-heating or pre-cooling the monitored space before the user arrives. The application server receives location data from the mobile device, determines that the user is approaching, and triggers the HVAC system to start adjusting the temperature in advance, so that the setpoint temperature is reached by the time the user enters the space.
Solution Approach 2:
The system makes the setback temperature dynamic rather than fixed. The control station adjusts the setback temperature based on the predicted arrival time of the user. When the user is expected to return soon, the setback temperature is set closer to the setpoint temperature to enable faster recovery. When the user will be away longer, the setback temperature is set farther from the setpoint to maximize energy savings.
2Ease of operation
If the comfort level temperature is set close to the setpoint temperature for satisfactory comfort, then user comfort is improved, but energy savings are insufficient
Solution Approach 1:
The system performs preliminary action by detecting user approach and pre-adjusting the temperature to the setpoint level before the user arrives. This allows the system to maintain a lower setback temperature (farther from setpoint) during unoccupied periods for energy savings, while ensuring comfortable temperature is restored in advance of user return.
Solution Approach 2:
The system dynamically adjusts between comfort level and setback level based on occupancy detection. When the user is detected approaching or present, the system transitions to comfort level (setpoint temperature). When the user is absent, the system transitions to setback level (energy-saving temperature). This dynamic switching resolves the contradiction by providing both comfort when needed and energy savings when possible.
3Loss of energy
If the HVAC system operates with insufficient time to recover from setback temperature, then energy savings are improved, but short cycling occurs causing equipment damage
Solution Approach 1:
The system performs preliminary action by calculating the predicted arrival time of the user and triggering HVAC operation in advance. The application server determines when the user will arrive based on location data, and the control station starts the HVAC system early enough to ensure complete temperature recovery before the user enters, preventing short cycling while maintaining energy efficiency.
Solution Approach 2:
The system uses feedback from temperature sensors and user location data to adjust HVAC operation. The control station monitors the actual temperature recovery process and compares it with the predicted timeline. If recovery is progressing slower than expected, the system extends operation time to ensure complete recovery, preventing short cycling while adapting to actual system performance.
4Productivity
If the heated water supply is planned based on projected user numbers, then resource allocation is optimized, but inaccurate projections lead to inadequate or excessive water supply
Solution Approach 1:
The system uses feedback from actual mobile device location data to continuously update and refine water consumption projections. The application server receives real-time location information from users, compares it with projected occupancy numbers, and adjusts water supply predictions accordingly. This feedback loop improves measurement precision over time while maintaining optimized resource allocation.
Solution Approach 2:
The system performs preliminary action by generating advance projections of user occupancy and water consumption needs. The application server analyzes scheduled arrivals and departures to predict future occupancy levels, allowing the water heating system to be pre-configured with appropriate capacity settings before peak demand occurs, ensuring adequate supply without excessive waste.
Data Source
AI summary
A system and method is used to characterize a user with properties, such as location in relation to established geo-fences, speed of traverse, projected traveling time required for a particular distance, etc. Those properties contribute to yielding a quantitative result in the calculated lead time period prior to the user arriving at a monitored space, including but not limited to a rented room in a hotel, and a house. The method uses the user's arrival time to estimate the setback temperature, which is the indoor temperature of a monitored space maintained during unattended time periods. The method also uses the user's arrival time to estimate the heated water volume to be provided, as well as, to house watch other property management interests.