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首页> 外文会议>Biennial International Pipeline Conference(IPC 2004) vol.3; 20041004-08; Calgary(CA) >FUEL-EFFICIENT OPERATION OF COMPRESSOR STATIONS USING SIMULATION-BASED OPTIMIZATION
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FUEL-EFFICIENT OPERATION OF COMPRESSOR STATIONS USING SIMULATION-BASED OPTIMIZATION

机译：利用基于仿真的优化实现压缩机站的高效节能

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摘要

One of the primary concerns in the operation of a compressor station is minimization of fuel consumption while maintaining the desired throughput of natural gas. In practice, the station operator tries to achieve this by shutting down units or controlling individual unit speeds based on experience. This is generally a trial-and-error process without any guarantee of optimality. In this paper we present a robust structured solution process for tackling this problem using simulation-based optimization. The first step to develop this solution process is to devise an analysis scheme that provides the simulation support required by the optimization. This was achieved by developing a fully implicit finite difference formulation of the continuity, momentum and energy equations for flow under non-isothermal conditions. The performance of each compressor unit was modeled by fitting polynomials to the compressor map. These polynomial equations were appended to the flow equations to obtain a complete set of system governing equations. The nonlinear algebraic equations resulting from this formulation were then solved using a Newton-Raphson iteration to obtain system performance. The problem of optimizing the operation of a compressor station was then formulated as a nonlinear programming problem (NLP) in which the design variables are the compressor unit speeds and the objective function to be minimized is the fuel consumption. A constraint was also placed on the minimum mass flow rate through the station to ensure that adequate flow is maintained while minimizing fuel consumption. This NLP was then solved using a sequential unconstrained minimization technique (SUMT) with a derivative-free grid search for handling the unconstrained minimizations. The simulation algorithm mentioned earlier is invoked whenever the optimization needs to evaluate the system response at a candidate operating point. The results obtained show that the simulation works very well in terms of predicting system response, and the proposed simulation-based optimization approach is highly effective in minimizing fuel consumption in a systematic way. The approach is successfully applied to single stations as well as to a sequence of stations along a pipeline, thereby establishing its applicability to station-level and network-level optimization.
机译：压缩机站操作中的主要问题之一是在保持所需的天然气通过量的同时将燃料消耗最小化。在实践中，站点操作员试图通过关闭设备或根据经验控制单个设备的速度来实现这一目标。通常，这是一个反复试验的过程，没有任何最优性的保证。在本文中，我们提出了一个健壮的结构化解决方案过程，该过程使用基于仿真的优化来解决此问题。开发此解决方案过程的第一步是设计一种分析方案，以提供优化所需的仿真支持。这是通过开发非等温条件下流动的连续性，动量和能量方程的完全隐式有限差分公式来实现的。通过将多项式拟合到压缩机映射图来建模每个压缩机单元的性能。将这些多项式方程附加到流动方程中，以获得一套完整的系统控制方程。然后使用牛顿-拉夫森迭代法求解由该公式产生的非线性代数方程，以获得系统性能。然后，将优化压缩机站运行的问题表述为非线性规划问题（NLP），其中设计变量是压缩机单位转速，而要最小化的目标函数是燃料消耗。还限制了通过工作站的最小质量流量，以确保维持足够的流量，同时将燃料消耗降至最低。然后使用顺序无约束最小化技术（SUMT）和无导数网格搜索来解决此NLP，以处理无约束最小化。每当优化需要在候选工作点评估系统响应时，就会调用前面提到的仿真算法。所得结果表明，该仿真在预测系统响应方面非常有效，并且所提出的基于仿真的优化方法在以系统方式将燃油消耗最小化方面非常有效。该方法已成功应用于单个站点以及沿管道的一系列站点，从而确立了其对站点级和网络级优化的适用性。

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