Climate control adaptive temperature setpoint adjustment systems and methods
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Solution Overview
Problem
Traditional climate control systems, such as HVAC systems, often operate inefficiently when a building is unoccupied, as they maintain stringent temperature setpoints, leading to increased energy consumption and operational costs due to fixed schedules rather than adaptive adjustments based on occupancy and environmental conditions.
Innovation Solution
A climate control system that includes an indoor temperature sensor and a control system capable of determining an expected return time to the building, adjusting the temperature setpoint dynamically based on historical occupancy and performance data to optimize energy usage by selecting from candidate schedules that balance energy consumption and operational efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the temperature setpoint is maintained at a stringent level when the building is unoccupied, then the building is ready for occupancy immediately upon return, but energy consumption increases unnecessarily
Solution Approach 1:
The system dynamically adjusts the temperature setpoint based on occupancy status and predicted return time. When the building is unoccupied, the setpoint is relaxed to reduce energy consumption. The control system transitions from static to dynamic temperature management, allowing the setpoint to vary over time based on occupancy predictions and environmental conditions.
Solution Approach 2:
The system performs preliminary cooling or heating before the predicted occupancy return time. By using historical occupancy data and environmental forecasts, the control system pre-adjusts the temperature to ensure comfort is ready upon return, rather than maintaining stringent temperatures continuously. This anticipatory approach reduces energy waste during unoccupied periods.
2Use of energy by moving object
If the temperature setpoint is relaxed during unoccupied periods, then energy consumption is reduced, but the building may not reach desired temperature by return time
Solution Approach 1:
The system performs preliminary temperature adjustment before the predicted occupancy return time. By using historical occupancy data and environmental forecasts, the control system pre-cools or pre-heats the building during unoccupied periods, ensuring the desired temperature is reached by return time without maintaining stringent setpoints continuously.
Solution Approach 2:
The control system uses feedback from historical performance data, occupancy patterns, and environmental conditions to optimize the temperature adjustment strategy. The system learns from past performance to predict future conditions and adjusts the setpoint trajectory accordingly, ensuring temperature readiness while minimizing energy consumption.
3Ease of operation
If a fixed temperature schedule is used, then the system operation is simple and reliable, but it cannot adapt to varying occupancy patterns and environmental conditions
Solution Approach 1:
The system transitions from a fixed, static temperature schedule to a dynamic, adaptive schedule that responds to varying occupancy patterns and environmental conditions. The control system uses historical data and predictions to adjust setpoints in real-time, maintaining simplicity in operation while significantly improving adaptability to changing conditions.
Solution Approach 2:
The system uses its own historical performance data and occupancy patterns to automatically adjust its operation without requiring manual intervention. By learning from past behavior and environmental responses, the system self-optimizes its temperature schedule, maintaining ease of operation while achieving high adaptability to varying conditions.
Data Source
AI summary
The present disclosure presents techniques for improving operational efficiency of climate control systems. A climate control system may include climate control equipment, a sensor that measures temperature in a building, and a control system that controls operation of the equipment using a first temperature schedule, which associates each time step with a temperature setpoint, when the building is occupied. When not occupied, the control system determines an expected return time based on historical occupancy data associated with the building, determines the temperature setpoint associated with the expected return time, determines candidate schedules each expected to result in the inside air temperature meeting the temperature setpoint, determines efficiency metrics each associated with one of the candidates based on historical performance data resulting from previous operation of the climate control system, and controls operation of the equipment based on a second temperature schedule selected from the candidates based on associated efficiency metrics.