Operation-Centric Process Modeling for Real-Time Plant Control
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Solution Overview
Problem
First-principles models are not widely used for online and operation-centric applications in the process industry due to their unsuitability for real-time decision-making, lack of easy calibration, and mismatch with physical plant equipment, making them challenging for real-time optimization and control of plant operations.
Innovation Solution
A method to dynamically transform a wide-scope first-principles model into an operation-centric model for a single operating unit, enabling real-time calibration and deployment, using flow and temperature reconciliations, feed estimations, and hydraulic model tuning to support automated control and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If a first-principles model is used for offline process design and rating, then the model is more rigorous and has better predictive power, but the model is not suitable for online real-time decision-making and control
Solution Approach 1:
The patent segments the plant-wide first-principles model into multiple unit-operation-specific models. Each unit model focuses on a specific operating unit (e.g., distillation column, heat exchanger) and includes only the equations and parameters relevant to that unit. This segmentation makes the models computationally efficient for real-time online use while maintaining the rigor and predictive power of first-principles approaches.
Solution Approach 2:
The patent applies local quality by tailoring each unit model to the specific characteristics and requirements of its corresponding operating unit. Each model is calibrated with unit-specific instrumentation information, control objectives, and physical dimensions, making it locally optimized for online decision-making and control at that specific unit while preserving the overall predictive accuracy.
2Reliability
If an offline first-principles model is developed for process design, then the model encapsulates fundamental principles, but the model lacks instrumentation information and does not reflect control objectives
Solution Approach 1:
The patent performs preliminary action by pre-calibrating each unit model with instrumentation information, control objectives, and operating parameters before online deployment. The models are prepared with the necessary calibration data and configuration during an offline setup phase, enabling them to be directly applied for real-time decision-making without requiring extensive adaptation when deployed online.
3Measurement precision
If a first-principles model is used for operation-centric applications, then high fidelity is required for accurate predictions, but the model is not scalable for hydraulic and thermodynamic calibrations
Solution Approach 1:
The patent segments the complex plant-wide model into smaller unit models, each handling specific hydraulic and thermodynamic calibrations for its operating unit. This segmentation reduces calibration complexity by limiting the scope of each calibration task to unit-specific parameters and measurements, while maintaining high prediction accuracy through focused, unit-optimized models.
Data Source
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AI summary
Embodiments are directed to computer methods and systems that construct a calibrated operation-centric first-principles model suitable for online deployment to monitor, predict, and control real-time plant operations. The methods and systems identify a plant- wide first-principles model configured for offline use and select a modeled operating unit contained in the plant- wide model. The methods and systems convert the plant- wide model to an operation-centric first-principles model of the selected modeled operating unit. The methods and systems recalibrate the operation-centric model to function using real-time measurements collected by physical instruments of the operating unit at the plant. The recalibration may include reconciling flow and temperature, estimating feed compositions, and tuning liquid and vapor traffic flow in the model. The methods and systems deploy the operation-centric model to calculate KPIs using real-time measurements and employ the KPIs to automatically (by a processor) predict and control behavior of the physical operating unit at the plant.