Compressor Rack Capacity Staging for Stable Suction Pressure
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Solution Overview
Problem
Existing refrigeration systems with multiple compressors face challenges in optimal control and efficient operation, particularly when managing variable capacity components and avoiding unpredictable suction pressure oscillations due to concurrent operation of multiple pulse width modulated devices.
Innovation Solution
A control algorithm that designates a single variable capacity component as the active component, operated in a variable capacity state, while others are switched to fixed stages, using neural networks to evaluate system load and select components for activation or deactivation to maintain accurate capacity control and minimize switching.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If multiple variable capacity components operate concurrently, then system flexibility is improved, but unpredictable suction pressure oscillations occur
Solution Approach 1:
The patent extracts the variable capacity modulation function from multiple components and concentrates it in a single designated component. This eliminates the harmful interaction between multiple pulse width modulated devices while preserving the flexibility benefit through neural network-based component selection and capacity adjustment.
Solution Approach 2:
The control system segments the compressor rack operation into fixed capacity components and one variable capacity component. This segmentation allows the system to maintain flexibility through the variable component while avoiding the oscillation problems that arise from concurrent modulation of multiple components.
2Productivity
If multiple compressors are used, then system capacity is improved, but control complexity increases
Solution Approach 1:
The neural network controller serves multiple functions: it selects which component operates in variable capacity mode, determines the appropriate capacity level, and manages the coordination between fixed and variable components. This universal control approach simplifies the overall system despite having multiple compressors.
Solution Approach 2:
The system changes the operational parameters of compressors by designating one component for variable capacity operation while keeping others at fixed capacity. This parameter differentiation reduces control complexity by creating a clear hierarchy in the control strategy.
3Loss of energy
If variable capacity components are used, then energy efficiency is improved, but component switching frequency increases
Solution Approach 1:
The neural network performs preliminary evaluation of system load and component states to predict the optimal variable capacity component before operation changes are needed. This advance planning reduces unnecessary switching by selecting components that are already running or will be running soon.
Solution Approach 2:
The system uses feedback from neural network evaluation of system load, component run-time, and capacity range to make intelligent switching decisions. This feedback mechanism minimizes switching frequency by only changing components when truly necessary for energy efficiency.
Data Source
AI summary
A system and method of controlling a compressor rack having a plurality of variable capacity components is provided. A variable capacity component is selected from the plurality of variable capacity components as a designated variable capacity component. The designated variable capacity component is operated by varying a capacity of the designated variable capacity component. Each variable capacity component of the plurality of variable capacity components, except for the designated variable capacity component, is operated at a fixed capacity corresponding to one of a maximum and a minimum capacity of the variable capacity component.