Parallel Gas Compressor Load Sharing via Decoupled Control
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Solution Overview
Problem
Conventional gas compressing systems with multiple parallel compressors require dedicated controllers for each compressor, leading to complex control loops and suboptimal efficiency and stability in pressure and flow control.
Innovation Solution
A gas compressing system with a single process controller, an adaptive load sharing optimizing controller, and speed demand computation modules, which decouples feedback and adaptation control loops, eliminating the need for individual load sharing controllers and optimizing energy efficiency by calculating compressor load split parameters and speed signals based on suction and discharge pressures and flows.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If dedicated PI or PID controllers are used for each compressor, then pressure and flow control can be maintained, but the control system complexity increases and dynamic performance deteriorates
Solution Approach 1:
The patent merges multiple dedicated controllers into a single centralized controller that manages all parallel compressors. This controller implements a unified control algorithm that decouples feedback and adaptation loops, achieving stable pressure and flow control without requiring individual controllers for each compressor, thereby reducing overall system complexity.
Solution Approach 2:
The single controller is designed to perform multiple functions: it manages pressure control, flow control, load sharing optimization, and coordination of multiple compressors simultaneously. This multi-functional approach eliminates the need for separate dedicated controllers while maintaining control stability.
2Ease of operation
If multiple dedicated controllers are used for each compressor, then individual control is achieved, but energy efficiency optimization becomes suboptimal
Solution Approach 1:
The controller implements a feedback mechanism that continuously monitors the operating conditions of all compressors and dynamically adjusts their load sharing ratios. This feedback-driven optimization ensures that compressors operate at peak efficiency points, reducing overall system energy consumption while maintaining individual compressor controllability.
Solution Approach 2:
The control system dynamically adjusts the load distribution among compressors based on real-time operating conditions. The adaptation loop continuously optimizes the operating points of individual compressors to maximize energy efficiency, transforming static individual control into dynamic optimized control.
3Ease of manufacture
If coupled control loops are used in conventional systems, then control implementation is straightforward, but dynamic performance and stability deteriorate
Solution Approach 1:
The control algorithm segments the control functions into two distinct decoupled loops: a feedback control loop for maintaining setpoint accuracy and an adaptation loop for optimizing performance. This segmentation improves dynamic response and stability by preventing interactions between control actions, while the unified implementation keeps the system manageable.
Data Source
AI summary
A gas compressing system including a plurality of n compressors connected in parallel. Each compressor has a suction line connected to a common suction manifold and a discharge line connected to a common discharge manifold configured to deliver compressed gas to a downstream load. The system also includes a process controller configured to control an average speed of the compressors based upon a discharge pressure in the common discharge manifold or a discharge flow through the common discharge manifold. The system further includes an adaptive load sharing optimizing controller configured to determine the speed of each compressor in the plurality of n compressors. A method of controlling a gas compressing system is also provided.