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Efficient operation of natural gas transmission systems: A network-based heuristic for cyclic structures

机译:天然气传输系统的高效运行:基于网络的循环结构启发式算法

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In this paper we propose a heuristic solution procedure for fuel cost minimization on gas transmission systems with a cyclic network topology, that is, networks with at least one cycle containing two or more compressor station arcs. Our heuristic solution methodology is based on a two-stage iterative procedure. In a particular iteration, at a first stage, gas flow variables are fixed and optimal pressure variables are found via dynamic programming. At a second stage, pressure variables are fixed and an attempt is made to find a set of flow variables that improve the objective function by exploiting the underlying network structure. Empirical evidence supports the effectiveness of the proposed procedure outperforming the best existing approach to the best of our knowledge. Gas transmission network problems differ from traditional network flow problems in some fundamental aspects. First, in addition to the flow variables for each arc, which in this case represent mass flow rates, a pressure variable is defined at every node. Second, besides the mass balance constraints, there exist two other types of constraints: (ⅰ) a nonlinear equality constraint on each pipe, which represents the relationship between the pressure drop and the flow; and (ⅱ) a nonlinear non-convex set which represents the feasible operating limits for pressure and flow within each compressor station. The objective function is given by a nonlinear function of flow rates and pressures. In the real world, these type of instances are very large both in terms of the number of decision variables and the number of constraints, and very complex due to the presence of nonlinearity and non-convexity in both the set of feasible solutions and the objective function.
机译:在本文中,我们提出了一种启发式解决方案,用于在具有循环网络拓扑的气体传输系统(即具有至少一个循环的网络包含两个或多个压缩机站弧)的情况下使燃料成本最小化。我们的启发式解决方案方法基于两阶段的迭代过程。在特定的迭代中,在第一阶段,固定气流变量,并通过动态编程找到最佳压力变量。在第二阶段,固定压力变量,并尝试找到一组流量变量,以通过利用底层网络结构来改善目标函数。经验证据支持拟议程序的有效性,优于我们现有的最佳方法。气体传输网络问题在某些基本方面不同于传统的网络流量问题。首先,除了每个电弧的流量变量(在这种情况下代表质量流率)之外,还在每个节点处定义压力变量。其次,除了质量平衡约束外,还有两种其他类型的约束:(each)每条管道上的非线性等式约束,它表示压降与流量之间的关系; (ⅱ)非线性非凸集,代表每个压缩机站内压力和流量的可行运行极限。目标函数由流速和压力的非线性函数给出。在现实世界中,这些类型的实例无论在决策变量的数量还是约束的数量上都非常大,并且由于在可行解集和目标集中都存在非线性和非凸性而非常复杂功能。

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