Climate control adaptive temperature setpoint adjustment systems and methods
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Solution Overview
Problem
Existing climate control systems face inefficiencies due to stringent temperature setpoints, leading to increased energy consumption and operational costs, especially when buildings are unoccupied.
Innovation Solution
A control system dynamically adjusts temperature schedules based on historical data and predicted occupancy to optimize energy usage and efficiency by selecting candidate schedules that minimize energy consumption while ensuring target temperatures are met at the expected return time.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a stringent temperature setpoint is maintained when the building is unoccupied, then the target temperature is met (comfort requirement), but energy consumption increases
Solution Approach 1:
The system performs preliminary actions by pre-cooling or pre-heating the building before the expected occupant return time. The controller predicts when occupants will return based on historical data and adjusts the temperature setpoint in advance, allowing the HVAC system to reach the target temperature before occupancy resumes, thereby maintaining comfort while reducing energy consumption during unoccupied periods
Solution Approach 2:
The system dynamically adjusts the temperature setpoint based on occupancy status and predicted return times. Instead of maintaining a fixed stringent setpoint, the controller modifies the setpoint dynamically - relaxing it during unoccupied periods and restoring it before expected occupancy, thus adapting the temperature control to actual operational needs and reducing unnecessary energy consumption
2Use of energy by moving object
If the temperature setpoint is increased when unoccupied to reduce energy consumption, then energy efficiency improves, but the temperature may not be met when occupants return
Solution Approach 1:
The controller predicts occupant return time using historical occupancy data and performs preliminary temperature adjustment before the predicted return. By pre-cooling or pre-heating the building to the target setpoint before occupants are expected to return, the system ensures temperature compliance is met while allowing energy-saving relaxed setpoints during unoccupied periods
Solution Approach 2:
The system uses historical occupancy data and actual temperature measurements as feedback to continuously improve its predictions and control strategy. The controller monitors whether the predicted return time and temperature adjustments are accurate, and refines its algorithm accordingly, ensuring that temperature setpoint compliance is reliably achieved while maximizing energy savings
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.