Industrial Gas Plant Configuration for Variable Renewable Power
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Solution Overview
Problem
The variability and intermittency of renewable energy sources like wind, solar, and tidal power pose challenges in designing industrial gas plants that can efficiently, safely, and cost-effectively produce gases such as hydrogen and ammonia, as these plants require a constant power supply to operate efficiently and sustainably.
Innovation Solution
A method and system that use a computational model to select a design configuration for an industrial gas plant complex powered by renewable energy sources, incorporating predicted time series power profiles and operational constraints to optimize the production of industrial gases by selecting suitable renewable power and plant subsystems, and generating designs that maximize operational output while meeting predefined constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If renewable energy sources (wind, solar, tidal) are used to power industrial gas plants, then environmental sustainability and cost-effectiveness are improved, but the variable and intermittent nature of these power sources causes operational instability and reduces production reliability
Solution Approach 1:
The patent implements dynamic configuration of the industrial gas plant complex, allowing subsystems to be selectively activated or deactivated based on real-time renewable power availability. The system dynamically adjusts operational parameters and reconfigures process flows to match variable power input, transforming the plant from a static to a dynamic system that adapts to changing energy conditions while maintaining reliable gas production.
Solution Approach 2:
The system changes operational parameters such as production rates, subsystem activation states, and process conditions based on the variable power input from renewable sources. By continuously adjusting these parameters in response to power availability, the plant maintains optimal efficiency and reliability despite the intermittent nature of wind, solar, and tidal power sources.
2Adaptability or versatility
If the industrial gas plant complex is designed to handle variable renewable power input, then adaptability to renewable energy sources is improved, but the design complexity and computational requirements increase significantly
Solution Approach 1:
The patent segments the industrial gas plant complex into multiple independent or semi-independent subsystems that can be individually configured, activated, or deactivated. This segmentation allows the complex adaptive behavior to emerge from simpler subsystem interactions, reducing overall design complexity while maintaining flexibility. Each subsystem can be optimized independently for specific operational modes.
Solution Approach 2:
The system employs partial configuration activation, where only the necessary subset of subsystems is activated based on current power availability and production requirements. Rather than designing for full capacity operation under all conditions, the system uses partial actions - activating only needed components - which simplifies the operational complexity while maintaining adaptability to varying renewable power inputs.
3Productivity
If computational optimization methods are used to select plant configurations, then production efficiency and output maximization are improved, but the computational time and processing requirements increase
Solution Approach 1:
The patent pre-calculates and stores optimal configuration solutions for various renewable power input scenarios and operational conditions. When the system needs to determine the best configuration, it retrieves pre-computed solutions rather than performing full optimization calculations in real-time. This preliminary action significantly reduces computational time during operation while maintaining high production efficiency.
Solution Approach 2:
The system uses surrogate models that replicate the behavior of complex optimization algorithms with simplified computational representations. These surrogate models provide approximate but sufficiently accurate configuration recommendations much faster than full computational optimization, enabling rapid decision-making while maintaining near-optimal productivity.
Data Source
AI summary
A method and system for selecting a design configuration of an industrial gas plant complex comprising one or more industrial gas plants and powered by one or more renewable power sources.