Chiller Control Using Dynamic Modeling for Free Cooling Mode Selection
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Solution Overview
Problem
Chilled water plants face inefficiencies in switching between mechanical cooling, free cooling, and integrated free cooling modes due to reliance on static outdoor air wet bulb temperature, lacking dynamic modeling to optimize performance and energy savings.
Innovation Solution
A chiller control system that uses dynamic modeling for a cooling tower, heat exchanger, and pump models to determine the optimal operating mode between mechanical cooling, free cooling, and integrated free cooling, adjusting parameters like fan speed and flow rates based on energy consumption and temperature predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If static outdoor air wet bulb temperature is used to determine mode switching, then the control system is simple, but the system efficiency and energy savings are suboptimal
Solution Approach 1:
The patent applies dynamics by transitioning from static temperature-based mode switching to dynamic modeling that continuously evaluates system state variables (water temperatures, flow rates, ambient conditions) to determine optimal operating modes. The controller dynamically adjusts condenser water flow rate and tower fan speed based on real-time model predictions, enabling the system to adapt to changing conditions and maximize efficiency.
Solution Approach 2:
The patent changes parameters by using multiple dynamic input variables (condenser water inlet temperature, chilled water temperatures, flow rates, ambient wet bulb temperature) instead of a single static temperature parameter. The model predicts performance across different operating parameters and selects modes based on comprehensive parameter evaluation rather than simple threshold comparisons.
2Use of energy by moving object
If dynamic modeling is implemented to optimize performance, then system efficiency and energy savings improve, but the device complexity increases
Solution Approach 1:
The patent replaces complex mechanical control systems with a computational thermal model. Instead of using complex hardware-based control mechanisms, the system uses software-based thermal modeling to predict performance and determine optimal operating modes. This substitution of mechanical/control complexity with computational algorithms achieves optimization while managing overall system complexity.
Solution Approach 2:
The patent creates a virtual copy of the physical cooling system through thermal modeling. The model replicates the thermal behavior of the condenser, cooling tower, and heat exchanger, allowing the controller to simulate and evaluate different operating scenarios without physically implementing complex control hardware. This virtual copying enables sophisticated optimization with minimal additional physical complexity.
3Ease of operation
If tower water flows are held constant in free cooling mode, then the control is simple, but optimization between tower fan power and pump power cannot be achieved
Solution Approach 1:
The patent applies dynamics by making tower water flow rate a dynamic variable rather than a constant. The model evaluates the relationship between tower fan power consumption and pump power consumption, dynamically adjusting the condenser water flow rate to optimize total energy consumption. This dynamic adjustment allows the system to find the optimal balance between fan and pump energy usage based on real-time conditions.
Solution Approach 2:
The patent changes the parameter of tower water flow rate from a fixed constant to a variable that is optimized by the thermal model. By allowing this parameter to change based on the balance between fan power and pump power requirements, the system achieves energy optimization while maintaining operational simplicity through automated model-based control.
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 enhances the efficiency and performance of chilled water plants by dynamically adjusting operating modes, reducing energy consumption and improving operational flexibility.
Implementation Method 1
free cooling using a cooling tower
Implementation Method 2
exchanging heat between a cooling tower circuit fluid and the chilled water
Implementation Method 3
exchanging heat between a cooling tower circuit fluid and the chilled water
Implementation Method 4
mechanical cooling (i.e. using a vapor compression circuit to absorb heat from the process fluid)
Data Source
AI summary
Chiller control systems and methods for chiller control use iterative modeling of cooling towers, heat exchangers, and pumps to determine the feasibility of integrated free cooling and the ability to take advantage of free cooling. The control systems and control methods can further include selecting the parameters for operating in the free cooling or integrated free cooling mode to improve efficiency and/or reduce energy consumption when operating in these modes. The models can have inputs and outputs that feed into one another, and converge at a solution over multiple iterations. The feasibility of integrated free cooling can be based on providing cooling to a cooling load process fluid at a heat exchanger. The availability of free cooling can be based on the cooling provided at the heat exchanger achieving a target temperature for the cooling load process fluid.


