Process Plant Control Configuration Using Offline Dynamic Models
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Solution Overview
Problem
Existing process plants face challenges in efficient control due to limited measurements, nonlinear dynamic responses, and the need for extensive testing and tuning of control strategies, which can lead to production losses and high costs.
Innovation Solution
A dynamic model based on thermo-fluidic and thermo-dynamic correlations is used to represent the process plant, allowing for online and offline modes of operation. In the online mode, it estimates unmeasured parameters and improves control strategies, while in the offline mode, it facilitates pre-tuning and configuration of control systems, reducing the need for on-site testing.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If extensive testing and tuning of control strategies is performed on-site, then control system reliability is improved, but production losses and costs increase
Solution Approach 1:
The control system is configured and tested before plant commissioning using a digital twin that replicates plant dynamics. Controller parameters are tuned offline using historical data and simulations, so that when the plant is commissioned, the control system is already optimized and requires minimal on-site testing, thereby reducing production losses and commissioning time while maintaining reliability
2Measurement precision
If detailed dynamic modeling is performed to improve control accuracy, then measurement precision is improved, but device complexity increases
Solution Approach 1:
A digital twin (virtual copy) of the process plant is created that replicates the plant's dynamics and behavior. This digital model uses available measurements and historical data to estimate unmeasured parameters through soft sensing algorithms, providing accurate parameter estimation without requiring complex physical measurement systems or invasive sensors in the actual plant
Data Source
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AI summary
The invention relates to a method for configuring a control system (300) for a process plant (100) using a dynamic model (200) of the process plant, the dynamic model (200) being based on at least one of thermo fluidic correlations, thermo dynamic correlations, phenomenological correlations, and equations, and being based on geometry and/or topology of components of the process plant, the dynamic model (200) receiving process parameters as input values, the dynamic model (200) being adapted to represent a transition from one to another state of the process plant (100), and the dynamic model (200) covering the entire operating range of the process plant (100), wherein the dynamic model is used in an offline mode, in which the dynamic model is used in stand-alone fashion, wherein, based on input (510) and output values (520) of the dynamic model (200), a behaviour of the process plant (100) is predicted, and wherein, based on the predicted behaviour of the process plant (100), the control system (300) is configured.