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Transient Optimization in Natural Gas Compressor Stations for Linepack Operation

机译：线性压缩机运行中天然气压缩机站的瞬态优化

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One of the key factors in the operation of a natural gas pipeline network is the linepack in the network. The desired operation of the network as derived from estimated receipts and deliveries is expressed in terms of the desired linepack profile that must be maintained. The compressor stations in the pipeline network are then operated in a manner that generates this linepack profile. Generally, the operating points selected for the units in the compressor stations are based on experience and experimentation and are therefore not optimal. In this paper, we present a systematic approach for operating the units of a compressor station to meet a specified linepack profile. The first step in developing this approach is the derivation of a numerical method for analyzing the flow through the pipeline under transient nonisothermal conditions. We have developed and verified a fully implicit finite difference formulation that provides this analysis capability. Next, the optimization of the compressor stations is formulated as a standard nonlinear programing problem in the following form: Find the values in the design variable vector denoted by b = [b_1,b_2,... ,b_n]~T, to minimize a given objective function F(b), subject to the constraints g_j(b) ≤0,j=1,... ,m. Here, n is the number of operational parameters whose optimal value is to be determined, while m is the number of operational constraints that must be enforced. In our formulation, the design variables are chosen to be the operating speeds of the units in the compressor stations, while the objective function is taken to be the average fuel consumption rate over the interval of interest, summed over all units. The constraint functions g_j(b) are formulated suitably to ensure that operational limits are met at the final solution that is obtained. The optimization problem is then solved using a sequential unconstrained minimization technique (SUMT), in conjunction with a directed grid search method for solving the unconstrained subproblems that are encountered in the SUMT formulation. The evaluation of the objective function and constraint functions at each step of the optimization is done by using the fully implicit analysis method mentioned above. A representative numerical example has been solved by the proposed approach. The results obtained indicate that the method is very effective in finding operating points that are optimal with respect to fuel consumption. The optimization can be done at the level of a single unit, a single compressor station, a set of compressor stations, or an entire network. It should also be noted that the proposed solution approach is fully automated and requires no user involvement in the solution process.
机译：天然气管道网络运行中的关键因素之一是网络中的管线组。从估计的收货和交货得出的网络的期望操作是根据必须维护的期望的线包配置文件表示的。然后，以生成该线包配置文件的方式操作管道网络中的压缩机站。通常，为压缩机站中的单元选择的工作点是基于经验和实验的，因此不是最佳的。在本文中，我们提出了一种系统的方法来操作压缩机站的单元，以满足指定的线组配置文件。开发此方法的第一步是推导一种数值方法，用于分析在瞬态非等温条件下通过管道的流量。我们已经开发并验证了提供这种分析功能的完全隐式有限差分公式。接下来，将压缩机站的优化公式化为以下形式的标准非线性规划问题：在设计变量矢量中找到由b = [b_1，b_2，...，b_n]〜T表示的值，以最小化a给定目标函数F（b），但要满足约束g_j（b）≤0，j = 1，...，m。在此，n是要确定其最佳值的操作参数的数量，而m是必须执行的操作约束的数量。在我们的公式中，设计变量被选择为压缩机站中机组的运行速度，而目标函数被视为目标间隔内的平均燃料消耗率，并将其汇总为所有机组。适当地制定约束函数g_j（b）以确保在所获得的最终解决方案中满足操作限制。然后，使用顺序无约束最小化技术（SUMT）结合有向网格搜索方法解决最优化问题，以解决SUMT公式中遇到的无约束子问题。通过使用上述完全隐式分析方法，可以在优化的每个步骤对目标函数和约束函数进行评估。所提出的方法已经解决了代表性的数值示例。所获得的结果表明，该方法对于找到相对于燃料消耗而言最佳的工作点非常有效。可以在单个单元，单个压缩机站，一组压缩机站或整个网络的级别上进行优化。还应注意，所提出的解决方案方法是完全自动化的，不需要用户参与解决过程。

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