Dynamic Gas Optimization via Smart Meter Feedback
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
The existing gas pipeline systems face challenges in dynamically optimizing gas composition, quality, and energy content to meet fluctuating customer demands and market prices, while also managing sudden changes or losses in gas sources and equipment failures, leading to unanticipated shutdowns and production losses.
Innovation Solution
A dynamic gas optimization system that utilizes smart meters and a communication and control network to monitor real-time gas values, calculate target values, and control valve settings across the pipeline network, allowing for predictive management and rebalancing of gas distribution, ensuring optimal supply and demand matching and minimizing costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If gas pipeline systems use traditional static control methods, then system simplicity is maintained, but the ability to dynamically optimize gas composition and meet fluctuating customer demands deteriorates
Solution Approach 1:
The patent implements dynamic control by enabling smart meters to continuously adjust valve settings based on real-time gas composition data and changing customer demands. The system transitions from static predetermined settings to dynamic adaptive control, allowing the pipeline network to respond to fluctuating market conditions and composition requirements automatically.
Solution Approach 2:
The system incorporates feedback mechanisms where smart meters monitor gas composition, quality, and energy content in real-time, compare actual values with target values, and automatically adjust flow control devices. This closed-loop feedback enables continuous optimization of gas distribution to meet customer specifications while adapting to changing conditions.
2Productivity
If the system implements real-time monitoring and dynamic control, then gas optimization and cost reduction are improved, but system complexity and measurement requirements worsen
Solution Approach 1:
The patent makes smart meters multi-functional by integrating composition sensing, real-time data processing, target value calculation, and flow control functions into single devices. This universal approach consolidates multiple separate systems into integrated smart meters, reducing overall system complexity while maintaining advanced optimization capabilities.
Solution Approach 2:
The system implements self-service through autonomous smart meters that automatically monitor gas parameters, calculate optimal target values, adjust valve settings, and rebalance gas distribution without human intervention. This automation improves productivity while the self-contained nature of smart meters prevents excessive complexity from centralized control systems.
3Reliability
If the system dynamically rebalances gas distribution, then production losses are reduced, but the complexity of detecting and measuring gas parameters worsens
Solution Approach 1:
The patent replaces complex mechanical measurement systems with electronic sensing and digital processing in smart meters. Electronic sensors and microprocessors enable precise measurement of gas composition, quality, and energy content with reduced mechanical complexity, improving reliability while managing measurement difficulty through electronic rather than mechanical means.
Data Source
AI summary
A system for optimally controlling gas flows in a pipeline network having gas import points, gas export points, and pipelines connected therebetween. The pipelines are interconnected by at least one junction. Each gas import point, gas export point and junction has a sensor and a flow control device, both of which correspond to a unique smart meter. Each smart meter includes a communication network interface and a flow control device controller. Each smart meter is capable of repeatedly: (1) receiving system gas data and first local gas request parameters from at least one other smart meter; (2) controlling the flow control device via the flow control device controller; (3) generating local gas values based on an output from the corresponding sensor; (4) calculating second local gas request parameters based on the local gas values and the system gas data; and (5) transmitting the system gas data.