Optimization Study of Gas Supply Pipeline Systems Based on Swarm Intelligence Optimization Algorithms
Source abstract
Abstract
With rapid urbanization and industrialization in China, existing gas supply networks urgently require renewal and optimization. This paper proposes a Gray Wolf Optimizer (GWO)-based method for reducing calculation errors and a Zebra Optimization Algorithm (ZOA)-based approach for gas supply pressure distribution. For error correction, the pipe friction coefficient is adjusted to minimize the deviation between calculated and actual flows. The GWO reduces average relative error to 0.01% with satisfactory iteration speed and efficiency. For pressure distribution, supply-end pressures are optimized to reduce energy consumption and enhance system performance. The ZOA shows strong convergence and global search capabilities. These methods provide valuable theoretical and practical insights for optimizing gas supply networks, supporting green transformation and sustainable development.
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Research context
OpenAlex topics: Advanced Algorithms and Applications · Metaheuristic Optimization Algorithms Research · Water Systems and Optimization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Utility Design Office, WISDRI Engineering& Research Incorporation Limited, Wuhan 430223, China
Technology Center, CCCC Second Harbor Engineering Co., Ltd., Wuhan 430040, China
School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
Hubei Key Laboratory for High-Efficiency Utilization of Solar Energy and Operation Control of Energy Storage System, Hubei University of Technology, Wuhan 430068, China
Funding
key Project of Hubei Province · Open Foundation of Hubei Key Laboratory for High-efficiency Utilization of Solar Energy and Operation Control of Energy Storage System
References (18)
Show source-provided references
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