Cold storage energy optimization systems
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Solution Overview
Problem
Current temperature-controlled storage systems waste energy by maintaining air temperature within a zone at a constant set-point, which does not accurately reflect the thermal mass and inertia of perishable goods, leading to unnecessary HVAC operation.
Innovation Solution
A system that develops a thermal profile for perishable goods, forecasts temperature changes, and adjusts the HVAC set-point to optimize energy efficiency by simulating the expected product temperature based on thermal mass, inertia, and other properties, allowing the goods to warm or cool within a specified range while minimizing energy usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If the HVAC system maintains air temperature at a constant set-point to prevent thermal abuse, then product temperature stability is improved, but energy consumption increases due to unnecessary cooling when thermal mass and inertia are sufficient
Solution Approach 1:
The system pre-cools or pre-heats perishable goods before they enter storage zones, using thermal mass and inertia to maintain temperature without continuous HVAC operation. This preliminary thermal conditioning allows the goods to self-regulate temperature during storage, reducing energy consumption while maintaining temperature stability.
Solution Approach 2:
The invention leverages the thermal mass and thermal inertia of the perishable goods themselves to maintain their temperature without continuous external energy input. The goods' inherent thermal properties enable them to resist temperature changes, making the system self-regulating and reducing reliance on energy-intensive HVAC operation.
2Device complexity
If point-in-time air temperature readings are used to control HVAC, then system simplicity is maintained, but measurement accuracy deteriorates because air temperature does not reflect actual product temperature
Solution Approach 1:
The system uses air temperature as an intermediary measurement that correlates with product temperature through thermal mass and inertia models. Rather than directly measuring product temperature (which would require complex embedded sensors), the system measures air temperature and uses computational models to infer product temperature, maintaining system simplicity while improving measurement accuracy.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach reduces energy consumption by optimizing HVAC operation, ensuring the goods remain within the desired temperature range while preventing thermal abuse, and provides a more efficient use of energy resources.
Implementation Method 1
operate a heating, ventilation, and air conditioning (HVAC) system to warm or cool the air within the zone
Implementation Method 2
operate a heating, ventilation, and air conditioning (HVAC) system to warm or cool the air within the zone
Implementation Method 3
the goods within the zone have a thermal mass and thermal inertia and may warm and cool at rates that are substantially different than the air surrounding it
Implementation Method 4
the goods within the zone have a thermal mass and thermal inertia and may warm and cool at rates that are substantially different than the air surrounding it
Data Source
AI summary
An energy optimization system for a load of perishable goods in temperature controlled storage, wherein a thermal profile of the load is developed, which is then used, in connection with temperature readings of the air and goods to simulate an expected temperature of the goods over an absolute or relative time duration at one or more set points. The simulation allows an optimal energy efficient set point to be determined, which may then be used to make the HVAC unit of the temperature controlled storage zone more energy efficient.