Fluid Separation Control System for Stable Transitions
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Solution Overview
Problem
Current control systems for fluid production units, such as air gas separation, face challenges in optimizing operations due to integration difficulties between optimization and control problems, leading to oscillations and inefficiencies in energy use, particularly in managing production transitions and equipment usage.
Innovation Solution
A method involving data collection and calculation to determine optimal operating points for fluid production units, incorporating predictive control and post-processing to validate solutions, ensuring stable transitions and minimizing energy consumption, while considering constraints and business rules.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If predictive control tools (MVPC or AFF) are used to manage production load variations, then the system can achieve a high degree of optimization and reach operating points close to constraints, but integration of optimization and control problems causes useless oscillations in transient phases and makes it difficult to use logic variables
Solution Approach 1:
The control system is divided into two independent modules: an optimization module that determines optimal operating points and a control module that executes transitions. This segmentation prevents the integration problems causing oscillations while maintaining high productivity through coordinated operation of separate modules.
Solution Approach 2:
A communication module acts as an intermediary between the optimization and control modules, transmitting information without direct integration. This intermediary approach allows the optimization module to provide target operating points to the control module without the control feedback causing oscillations in the optimization process.
2Use of energy by stationary object
If advanced predictive control strategies are implemented to optimize production, then energy consumption can be minimized and production constraints satisfied, but the system cannot determine optimal operating points that truly minimize energy use
Solution Approach 1:
The optimization module independently determines optimal operating points based on energy minimization criteria without being constrained by control module limitations. This self-service capability allows the system to identify true energy optima while the control module handles the practical aspects of reaching these points.
Solution Approach 2:
The optimization module performs preliminary calculation of optimal operating points before the control module executes transitions. This preliminary action allows energy minimization to be fully considered in determining targets, while the control module subsequently manages the actual transition without compromising the energy optimization objectives.
3Ease of operation
If control systems use fixed time intervals to send objectives to load change controllers, then implementation is simplified, but oscillations occur and non-optimal results are produced in non-stationary states
Solution Approach 1:
The system transitions from fixed time intervals to dynamic, demand-driven optimization cycles. The optimization module operates independently without being constrained by fixed control cycles, allowing it to respond dynamically to changing conditions and eliminate oscillations while maintaining ease of implementation through modular architecture.
Data Source
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AI summary
The invention relates to the optimized management of one or more fluid production units, especially those involving fluid separation treatment, comprising: a) a data collection step (10), the data being on one or more values of current parameters defining a current operating point of the production unit, on a future production demand and on at least one optimization criterion; and b) a computation step (12) for computing one or more parameters defining a new operating point of the unit, at least in accordance with this demand. The computation step b) comprises at least: 1) an estimation (12) of at least one optimum solution for defining the new operating point; and 2) a validity test (13) carried out on this optimum solution, at least in accordance with an analysis of the transition of the production unit from the current operating point to the new operating point.