Predictive Room Temperature Control Using Building Thermal Mass
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Solution Overview
Problem
Conventional room temperature control systems in buildings are inefficient in optimizing energy usage, leading to increased energy and cost requirements due to their inability to effectively integrate free and expensive energy sources, and often compromise comfort due to incorrect predictions and model errors.
Innovation Solution
A hierarchical control structure using predictive model control, where top-level control manages free energy sources like solar gains and free cooling, while lower-level control handles expensive energy sources, optimizing energy consumption through a building model and microcomputer optimization, with PID controllers for zone-specific control.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Use of energy by moving object
If conventional control arrangements are used to regulate room temperature, then temperature control function is provided, but energy costs increase and optimization of free cooling/heating is lost
Solution Approach 1:
The predictive control device performs preliminary actions by forecasting future thermal conditions and pre-adjusting the room temperature within the comfort range before expensive heating or cooling is needed. This allows the system to utilize free thermal energy sources and minimize consumption of expensive energy, thereby reducing energy costs while managing complexity through structured prediction algorithms
Solution Approach 2:
The control system is segmented into hierarchical levels: a predictive control level that handles strategic energy optimization and a lower-level control level that executes specific heating/cooling actions. This segmentation allows complex optimization tasks to be separated from simple execution tasks, reducing overall system complexity while enabling sophisticated energy management
2Use of energy by moving object
If model predictive control is used to optimize energy consumption, then energy costs are reduced, but control precision requirements increase due to model errors and disturbances
Solution Approach 1:
The system applies beforehand cushioning by maintaining the room temperature within a comfort range (e.g., 21°C to 26°C) rather than a single setpoint. This temperature band acts as a buffer that compensates for model errors and disturbances, allowing predictive control to optimize energy consumption without requiring extremely high prediction accuracy, as temporary deviations are tolerated within the comfort zone
Solution Approach 2:
The control system incorporates feedback mechanisms that continuously monitor actual temperature deviations and compare them with predicted values. This feedback is used to correct model errors and adjust future predictions, thereby improving energy optimization over time while maintaining acceptable control precision through iterative refinement rather than requiring perfect initial models
3Productivity
If a larger comfort temperature range is designed to enable predictive control, then energy efficiency improves, but temperature control precision is reduced
Solution Approach 1:
The system performs preliminary heating or cooling actions to store thermal energy in the building's thermal mass (walls, floors, furniture) while the room temperature remains within the expanded comfort range. This allows the building to naturally maintain comfortable temperatures during peak periods without active heating/cooling, improving energy efficiency while the actual temperature control precision is maintained through predictive adjustments
Solution Approach 2:
The system dynamically changes the target temperature parameter within the comfort range based on predictions of future thermal conditions. Instead of maintaining a fixed setpoint, the optimal temperature within the range is adjusted in real-time based on forecasted weather, occupancy patterns, and energy prices, thereby achieving high energy efficiency while maintaining precise temperature control through adaptive parameter optimization
Data Source
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AI summary
The inventive arrangement for controlling and regulating room temperature in a building which has a hierarchical structure comprising at least two floors (30; 31) is provided with a predictive device (24) which is arranged on the top floor (30) and is used for the optimal control of the use of at least one free energy source, and comprises at least one device (32, 33, 34) which is arranged on a lower floor (31) and which is used for the returned regulation of at least one additional energy source. The predictive device (24) comprises a building model (25) and means (26) for repeating the optimisation of the energy requirement or the energy costs. The regulation strategy of the predictive device (24) uses characteristics (25) of a passive heat accumulator of the building.