基于随机优化算法的天然气管道运行优化研究综述

Survey of research on natural gas pipeline operation optim ization based on stochastic optim ization algorithms

在“双碳”目标背景下,天然气管道的运行优化可以最大程度地实现降本增效减碳,因而得到了广泛且深度的关注。与确定性算法不同,随机优化算法在处理大规模管道和混合整数非线性规划问题上优于经典确定性算法。为此,对基于随机优化算法的天然气管道运行优化进行了调研。首先,介绍了天然气管道运行的数学模型;其次,采用随机优化算法求解模型最优调度结果,分别对遗传、粒子群、蚁群以及模拟退火4类算法在天然气管道运行中的应用进行了分析、对比和归纳。最后,对天然气管道运行优化的技术挑战与发展趋势进行了探讨。

Against the backdrop of China’s“dual-carbon”goals,the optimization of natural gas pipeline operations has attracted keen academic interest as it can effectively cut costs,improve efficiency,and help achieve carbon reduction.Stochastic optimization algorithms show advantages over classical deterministic algorithms in dealing with large-scale pipeline networks and mixed-integer nonlinear programming(MINLP)problems.This paper investigates the optimization of natural gas pipeline operations based on stochastic optimization algorithms.Firstly,a mathematical model for natural gas pipeline operations is built.Secondly,stochastic optimization algorithms are employed to achieve optimal scheduling results.Four types of algorithms including genetic algorithms,particle swarm optimization,ant colony optimization,and simulated annealing are employed to analyze,compare,and generalize their applications in natural gas pipeline operations.Finally,the technical challenges and development trends of natural gas pipeline network operation optimization technology are discussed.