Modelling of a distillation column with operating state changes
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Solution Overview
Problem
Current air separation installations operate statically, making it difficult to respond to fluctuating energy prices and varying demands, as existing methods fail to accurately predict the behavior of distillation columns under dynamic conditions, particularly with varying or absent feed fluid streams, affecting operability, load-changing rates, product quality, and energy efficiency.
Innovation Solution
A dynamic thermohydraulic simulation model for distillation columns with multiple stages, where the state is determined by pressure differences between stages, using a pressure-driven approach with coefficients of resistance and conductance values, allowing for dynamic operation and simulation of zero flows and flow reversals, enabling optimal control and energy management.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If air separation installations are operated statically with constant compressor power, then the system is simple to operate and stable, but it cannot respond to fluctuating energy prices and varying demands
Solution Approach 1:
The patent applies dynamics by transitioning from static operation to dynamic operation where the distillation column can adapt to varying demands and energy prices. The system uses a dynamic model that calculates time-dependent states, allowing the column to respond flexibly to changing operating conditions while maintaining stability through controlled transitions.
Solution Approach 2:
The patent implements parameter changes by varying the compressor power and feed stream characteristics dynamically. The model incorporates time-dependent parameters such as variable feed composition, flow rates, and pressure conditions, enabling the system to optimize performance according to real-time energy prices and demand fluctuations.
2Measurement precision
If existing steady-state models are used for distillation columns, then the models are simple to calculate, but they fail to accurately predict behavior under dynamic conditions with varying or absent feed fluid streams
Solution Approach 1:
The patent replaces traditional mechanical steady-state modeling approaches with a dynamic thermohydraulic simulation model. This substitution enables accurate prediction of column behavior under transient conditions, including start-up, shutdown, and varying feed conditions, by solving time-dependent mass and energy balance equations.
Solution Approach 2:
The patent applies preliminary action by developing a comprehensive dynamic model that anticipates and prepares for various operating scenarios. The model pre-calculates response characteristics for different feed conditions and energy price fluctuations, enabling operators to optimize performance before actual changes occur.
3Productivity
If the distillation column operates with varying feed fluid streams, then the system can adapt to different demands, but it becomes difficult to predict operability, maximum load-changing rates, and product quality
Solution Approach 1:
The patent implements feedback by using the dynamic model to continuously monitor and predict column response to feed variations. The model provides real-time information on operability limits, maximum load-changing rates, and product quality trends, enabling corrective actions to be taken before deviations occur.
Solution Approach 2:
The patent applies beforehand cushioning by using the dynamic model to identify and prepare for potential operability issues. The model predicts maximum load-changing rates and provides advance warning of potential problems, allowing operators to adjust conditions to maintain reliable operation.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
This approach allows for dynamic operation of air separation installations, optimizing energy use, responding to fluctuating energy prices, and improving the overall efficiency and product quality by simulating the behavior of distillation columns under varying conditions, including zero flows and flow reversals.
Implementation Method 1
both the gaseous and the liquid flows between the adjacent column stages are brought about by the pressure differences prevailing between the adjacent column stages
Implementation Method 2
a distillation column having multiple column stages for separating a feed fluid stream into individual fluid components
Implementation Method 3
determining a state of a distillation column having multiple column stages for separating a feed fluid stream into individual fluid components
Data Source
AI summary
A method is provided for determining a state of a distillation column having multiple column stages for separating a feed fluid stream into individual fluid components. The state is determined by means of a model in a manner dependent on pressure differences prevailing between adjacent column stages. In the model, both gaseous and liquid flows between adjacent column stages are brought about by the pressure differences prevailing between adjacent column stages. A substance quantity flow characterizing gaseous flow between two column stages is given by {dot over (N)}V·RV=CV·ΔpV. A substance quantity flow characterizing liquid flow between two column stages is given by {dot over (N)}L·RL=CL·ΔpL. ΔpV,L is a total pressure difference between two adjacent column stages. RV,L is a coefficient of resistance between two adjacent column stages and CV,L is a conductance value of flow between two adjacent column stages.