Arrival-Predictive HVAC and Water Heating Control for Setback Recovery
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Solution Overview
Problem
Conventional HVAC systems in hotels face inefficiencies due to inaccurate temperature recovery times and excessive energy consumption, leading to short cycling and equipment damage, while heated water supply is not optimally managed based on user arrival times and occupancy levels.
Innovation Solution
A user location tracking system using mobile devices with transmitters and an application server to determine user arrival times, calculate temperature drive times, and project heated water consumption, adjusting HVAC and water heater operations accordingly to optimize energy usage and extend equipment life.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of energy
If the setback temperature is set too far from the setpoint temperature to conserve energy, then energy savings increase, but the temperature recovery time becomes excessively long and comfort is compromised
Solution Approach 1:
The system performs preliminary actions by tracking user location and predicting arrival time in advance. Based on the predicted arrival time, the system proactively adjusts the setback temperature to optimize both energy savings and temperature recovery time, rather than using fixed temperature settings
Solution Approach 2:
The system dynamically adjusts the setback temperature based on real-time user location data and predicted arrival time. The setback temperature is not fixed but varies dynamically according to when the user is expected to return, allowing optimization of both energy consumption and temperature recovery time
2Loss of time
If the setback temperature is set too close to the setpoint temperature to ensure comfort, then temperature recovery time decreases, but energy savings are insufficient
Solution Approach 1:
The system performs preliminary actions by tracking user location and predicting arrival time in advance. Based on the predicted arrival time, the system proactively adjusts the setback temperature to optimize both energy savings and temperature recovery time, rather than using fixed temperature settings
Solution Approach 2:
The system dynamically adjusts the setback temperature based on real-time user location data and predicted arrival time. The setback temperature is not fixed but varies dynamically according to when the user is expected to return, allowing optimization of both energy consumption and temperature recovery time
3Stability of the object's composition
If the HVAC system operates frequently to maintain temperature (short cycling), then temperature stability improves, but equipment lifespan decreases due to excessive wear
Solution Approach 1:
The system performs preliminary actions by tracking user location and predicting arrival time in advance. Based on the predicted arrival time, the system proactively adjusts the setback temperature to optimize both energy savings and temperature recovery time, rather than using fixed temperature settings
Solution Approach 2:
The system uses periodic user presence patterns to determine when to activate HVAC operations. By scheduling operations based on predicted user arrival times rather than continuous operation, the system reduces unnecessary cycling while maintaining temperature stability when needed
4Quantity of substance
If heated water supply is increased to meet peak demand, then water availability improves, but energy consumption increases
Solution Approach 1:
The system performs preliminary actions by tracking user location and predicting arrival time in advance. Based on the predicted arrival time and number of users, the system proactively adjusts heated water supply to match actual demand, avoiding energy waste from heating excess water
Solution Approach 2:
The system uses real-time user location data and occupancy information as feedback to dynamically adjust heated water supply. The water heater operation is continuously optimized based on actual user presence and predicted arrival times, ensuring water availability while minimizing energy consumption
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.


