Electrolysis Plant Control Using 1D Multiphysics Stack Modeling
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Solution Overview
Problem
Existing diphasic flow models for low-temperature water electrolysis are not suitable for large-scale electrolysis plants due to their complexity and computational intensity, which makes them unsuitable for stack or plant-level simulations, and they require precise geometry and are computationally expensive, affecting their applicability in power systems.
Innovation Solution
A multiphysics model is proposed that includes a one-dimensional liquid-gas diphasic flow model coupled with an electrochemical model, allowing for simplified calculations and easy control of large-scale electrolysis plants by adapting operation parameters and executing control based on calculated values, specifically using a control module to manage auxiliary components like heaters and pumps.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing diphasic flow models (Euler-Euler, Euler-Lagrange, mixture models) are used for water electrolysis research, then the model can capture liquid-gas flow behavior and bubble effects on electrochemical reaction, but the model becomes highly nonlinear requiring CFD methods with precise geometry, making it suitable only for single cell modeling and not for stack or plant level electrolyzers
Solution Approach 1:
The patent segments the complex three-dimensional diphasic flow model into simplified one-dimensional models for individual flow channels. By dividing the electrolyzer stack into discrete channel segments and modeling each channel separately with reduced dimensional complexity, the system achieves computational tractability for stack-level applications while maintaining essential diphasic flow physics. This segmentation allows the model to be solved without full CFD while still capturing bubble effects on electrochemical reactions.
2Measurement precision
If existing diphasic flow models solve variables in the whole flow channel, then the model comprehensively captures flow behavior, but the computing scale is enlarged and computational cost increases
Solution Approach 1:
The patent extracts and focuses computational effort only on the critical regions where bubbles interact with electrodes in each flow channel. Instead of solving the complete three-dimensional diphasic flow field throughout the entire stack, the model extracts the essential physics from selected channel segments and uses these to represent the overall system behavior. This extraction approach maintains accuracy for electrochemical reaction modeling while dramatically reducing computational scale.
Solution Approach 2:
The patent applies partial action by modeling only the essential diphasic flow variables needed for electrochemical reaction prediction rather than solving for all flow channel variables. By focusing computational resources on the critical bubble-electrode interaction regions and using simplified one-dimensional formulations, the model achieves sufficient accuracy for system-level analysis without the excessive computational burden of complete CFD simulations.
3Reliability
If parameters of liquid and gas are strongly coupled in diphasic flow models, then the model accurately represents physical reality, but convergence of the model is worsened
Solution Approach 1:
The patent introduces dynamic adaptation of model parameters based on local flow conditions. The liquid and gas parameters are allowed to dynamically adjust according to void fraction and flow regime variations in each channel segment. This dynamic approach maintains physical accuracy by adapting to changing conditions while improving convergence through localized parameter adjustments rather than requiring global coupling of all liquid and gas parameters throughout the system.
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 enables efficient and fast control of electrolysis plants at the stack or plant level, reducing computational complexity and improving convergence, allowing for optimized bubble distribution and overall efficiency, and facilitates integrated simulations with power systems.
Implementation Method 1
a one-dimensional liquid-gas diphasic flow model
Implementation Method 2
water electrolysis, has been recognized as an essential element in future integrated energy systems
Data Source
AI summary
The present disclosure relates to a method and control module for operating an electrolysis plant (EP), an electrolysis plant, and a method for dispatching at least one electrolysis plant in a power system. The electrolysis plant comprises an electrolysis stack assembled from a plurality of electrolysis cells. The method for operating the electrolysis plant comprises, by a control module, adapting a multiphysics model to a plurality of operation parameters of the electrolysis plant. The multiphysics model comprises a one-dimensional liquid-gas diphasic flow model and an electrochemical model coupled with the diphasic flow model. The plurality of operation parameters comprises preset parameter(s) and parameter(s) to be calculated. A value of each parameter to be calculated is calculated according to a preset value of the preset parameter(s) by means of the multiphysics model. Control to the electrolysis plant is executed according to the calculated value of the parameter(s) to be calculated.