HVAC Setpoint Boundary Adjustment Using Occupant Feedback Data
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Solution Overview
Problem
HVAC systems struggle to maintain occupant comfort due to varying comfort preferences among occupants and changes in occupancy, weather, and seasons, as existing systems fail to adaptively adjust temperature setpoints in response to these dynamics.
Innovation Solution
An HVAC system with a setpoint adjustment controller that partitions occupant setpoint adjustment data into time period bins based on common attributes, counts the number of setpoint increases and decreases, and adjusts the setpoint boundaries accordingly, using thresholds to determine whether to increase, decrease, or maintain the setpoint boundaries to reflect changing occupant preferences and environmental conditions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the HVAC system uses fixed temperature setpoints, then the system operation is simple and energy consumption is predictable, but occupant comfort cannot adapt to changing preferences and environmental conditions
Solution Approach 1:
The patent implements dynamic setpoint boundaries that automatically adjust based on real-time monitoring of occupant temperature adjustments. The system transitions from static predetermined boundaries to dynamic adaptive boundaries that evolve with occupant preferences, allowing the HVAC system to adapt to changing comfort requirements without manual intervention
Solution Approach 2:
The system continuously monitors occupant temperature adjustments and uses this feedback to automatically modify setpoint boundaries. By closing the control loop with real-time feedback from occupant behavior, the system learns and adapts to individual and group comfort preferences, improving adaptability while maintaining automated operation
2Adaptability or versatility
If the HVAC system continuously adjusts setpoints to match individual occupant preferences, then occupant comfort is improved, but energy consumption increases and system control becomes more complex
Solution Approach 1:
The system adjusts setpoint boundaries partially rather than maximizing adaptation at all times. By modifying boundaries only when occupant adjustments indicate a need and within controlled increments, the system achieves sufficient adaptability to environmental conditions while avoiding excessive energy consumption that would result from continuous full-scale adjustments
Solution Approach 2:
The system changes the setpoint boundary parameters dynamically based on monitored occupant behavior and environmental conditions. By adjusting these parameters adaptively rather than maintaining fixed values, the system responds to environmental changes efficiently, optimizing energy use according to actual needs rather than through continuous operation
3Adaptability or versatility
If the system monitors and responds to every occupant temperature adjustment, then occupant comfort is maximized, but the control system complexity and data processing requirements increase
Solution Approach 1:
The system automatically monitors, analyzes, and adjusts setpoint boundaries without requiring external intervention or complex centralized control. The HVAC system serves itself by autonomously learning from occupant behavior patterns and making appropriate adjustments, reducing the need for complex external control infrastructure while maintaining high adaptability
Solution Approach 2:
The system divides the control function into manageable segments: monitoring occupant adjustments, analyzing comfort patterns, and adjusting setpoint boundaries. This segmentation of the control process simplifies the overall system architecture while enabling comprehensive adaptability to occupant preferences through modular, incremental operations
Data Source
AI summary
An HVAC system for automatically adjusting setpoint boundaries of a space includes building equipment configured to provide heating or cooling to the space to affect an environmental condition of the space and a controller. The controller obtains occupant setpoint adjustment data indicating occupant setpoint increases or occupant setpoint decreases at multiple times during a time interval and partitions the occupant setpoint adjustment data into time period bins based on the multiple times associated with the occupant setpoint adjustment data, each of the time period bins containing occupant setpoint adjustment data characterized by a common time attribute. The controller determines a number of occupant setpoint increases and a number of occupant setpoint decreases indicated by the occupant setpoint adjustment data within each time period bin and adjusts a setpoint boundary of the space based on the number of occupant setpoint increases or the number of occupant setpoint decreases.


