Natural Gas Network Optimization via Hybrid Variable Separation
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Solution Overview
Problem
Traditional methods for optimizing natural gas transport networks in steady state are inefficient, requiring manual calculation of optimal pressure and flow rates, and cannot automatically determine optimal settings for active works like compressors and valves, leading to suboptimal network performance and potential saturation issues.
Innovation Solution
A hybrid combinatorial and continuous optimization method that automatically determines optimal values for both continuous and discrete variables in a natural gas transport network by using a separation of variables technique to explore possible values and evaluate branches of a tree structure, minimizing an economic objective function while adhering to constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If traditional manual calculation methods are used to determine optimal pressure and flow rates, then calculation accuracy can be maintained, but the optimization process becomes time-consuming and cannot automatically determine optimal settings for active works
Solution Approach 1:
The system performs self-optimization by automatically determining optimal settings for compressors and valves without manual intervention. The optimization algorithm independently calculates and adjusts discrete variables (compressor states, valve positions) and continuous variables (pressures, flow rates) to minimize the economic objective function while satisfying network constraints.
Solution Approach 2:
Traditional manual calculation methods are replaced with an automated computational optimization system. The patent substitutes human operators with a computer-implemented algorithm that uses mathematical models and optimization techniques to rapidly determine optimal network configurations, eliminating the time-consuming nature of manual calculations.
2Productivity
If the network operates at maximum capacity to improve productivity, then economic efficiency increases, but the network becomes saturated and constraint violations occur
Solution Approach 1:
The optimization system dynamically adjusts network operating parameters to maintain optimal performance without saturation. By continuously calculating and adjusting discrete variables (compressor startup states, valve positions) and continuous variables (pressures, flow rates), the system adapts to changing conditions and maintains operation within constraint boundaries while maximizing economic efficiency.
Solution Approach 2:
The system performs preliminary optimization calculations to determine the optimal configuration before actual network operation. By pre-calculating the optimal states of compressors and valves along with corresponding pressure and flow rate distributions, the system prevents constraint violations before they occur, ensuring reliable operation at maximum sustainable capacity.
3Stress or pressure
If more compressors are activated to maintain pressure in extended network sections, then pressure constraints are satisfied, but energy consumption increases
Solution Approach 1:
The optimization system changes the operational parameters of compressors and valves to minimize energy consumption while maintaining pressure constraints. By adjusting discrete variables (which compressors are active) and continuous variables (pressure levels, flow rates), the system identifies the optimal configuration that satisfies minimum pressure requirements at consumption points while minimizing the total energy consumed by compression equipment.
Data Source
AI summary
The method of automatic optimization is applied to a natural gas transport network in the steady state comprising at one and the same time a set of passive works such as pipelines or resistances, and a set of active works comprising regulating valves, isolating valves, compression stations, storage or supply devices, consumption devices, elements for bypassing the compression stations and elements for bypassing the regulating valves, the passive works and the active works being linked together by junctions. The optimization method comprises the determination of values for continuous variables. Intervals of values for the continuous variables and sets of values for the discrete variables are chosen as initial state of the optimization. The possibilities of values for the variables are explored by constructing on the go a tree with branches linked to nodes describing the combinations of values envisaged by using a separation of variables and evaluation technique, the values of the quantities sought being considered to be optimal when predetermined constraints are no longer violated or are minimally violated and a predetermined objective function is minimized.