Building Cooling Control Using Predictive Comfort-Energy Optimization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing air conditioning systems face challenges in minimizing energy consumption without compromising occupant comfort, as maintaining comfortable temperatures often leads to high power consumption, and precisely matching occupant preferences at all times results in discomfort due to increased energy use.
Innovation Solution
A building cooling system that includes a system management circuit capable of optimizing the cooling capacity of devices over a time horizon, balancing power consumption and comfort terms through an objective function, which predicts indoor air temperature based on an efficiency model and adjusts the cooling capacity to minimize energy usage while maintaining comfort.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Temperature
If cooling capacity is increased to maintain comfortable temperatures, then occupant comfort is improved, but power consumption increases
Solution Approach 1:
The system performs preliminary cooling during off-peak hours when electricity rates are lower, storing cooling capacity in the building's thermal mass (walls, floors, furniture). This allows the system to pre-cool the building before peak demand periods, reducing the need for high power consumption during expensive hours while maintaining comfort.
Solution Approach 2:
The system dynamically adjusts cooling capacity based on real-time conditions including outdoor temperature, humidity, occupancy patterns, and electricity pricing signals. The control algorithm continuously optimizes the balance between comfort maintenance and energy consumption, adapting to changing conditions rather than operating at fixed capacity.
2Use of energy by moving object
If cooling capacity is reduced to minimize power consumption, then energy efficiency is improved, but occupant comfort deteriorates
Solution Approach 1:
The system continuously monitors indoor temperature, humidity, and occupancy conditions, using this feedback to adjust cooling capacity in real-time. When comfort thresholds are approached, the system automatically increases cooling, ensuring comfort is maintained while minimizing energy consumption through precise, condition-based control rather than continuous high-capacity operation.
Solution Approach 2:
The system changes operational parameters such as cooling capacity, runtime scheduling, and temperature setpoints based on external conditions including weather forecasts, electricity pricing, and occupancy patterns. This allows the system to operate at reduced capacity during favorable conditions while maintaining comfort when needed.
3Use of energy by moving object
If cooling capacity is precisely matched to immediate demand, then energy efficiency is improved, but future comfort is compromised due to lack of thermal buffer
Solution Approach 1:
The system proactively builds thermal storage in the building structure during periods of low demand or low electricity costs, creating a thermal buffer that can be drawn upon during peak periods. This preliminary action ensures both energy efficiency and comfort reliability by anticipating future needs rather than merely responding to current conditions.
Solution Approach 2:
The system dynamically determines the optimal balance between immediate cooling provision and thermal storage building, adjusting the charging/discharging rate of thermal mass based on forecasted conditions, electricity prices, and occupancy patterns. This dynamic approach maintains both efficiency and reliability by adapting to changing requirements.
Data Source
AI summary
A building cooling system includes one or more cooling devices operable to affect an indoor air temperature of a building and a system management circuit. The system management circuit is configured to obtain an objective function that includes a power consumption term and a comfort term, perform an optimization of the objective function over a time horizon to determine values of the cooling capacity of the cooling devices where each value of the cooling capacity corresponds to a time step of the time horizon, and control the cooling devices based on the values of the cooling capacity of the cooling devices. The comfort term of the objective function a difference between a prediction of the indoor air temperature of the building and a temperature setpoint for the building, while the power consumption term is a function of the power consumption of the one or more cooling devices.