成品油管道水击超前保护优化方案

Optimization scheme for advance protection against water hammer of products oil pipelines

成品油管道发生泵站意外停电事故后通常执行水击超前保护程序,该保护方案对管道的安全性有决定性影响。为了确保管道从事故前稳态安全平稳过渡到事故后较优的运行状态,需要制定最佳的水击超前保护方案。对成品油管道泵站意外停电水击工况进行分析,以水击事故发生后下一稳态时输量最大且各调节阀节流压力之和最小为目标,建立优化模型,相应的约束条件为全线不超压、不汽化。模型求解采取两种不同策略:事故站下游以各站出站压力最低为目标分别寻优,采用水力坡降线平移法求解;事故站上游以整体总节流最小寻优,为了提高求解速度,采用深度优先搜索法求解。以某成品油管道泵站意外停电事故工况为例,对该优化模型进行实例应用,并根据优化结果制定水击事故过渡过程的控制逻辑,并使用仿真软件SPS验证了控制逻辑的合理性,表明该优化模型合理可靠。

The procedure of advance protection against water hammer of products oil pipelines is generally implemented in the case of unplanned power failure of a pump station, which has a decisive influence on the safety of pipelines. To realize safe and smooth transition of pipelines from a steady state before the accident to a better operating state after the accident, an optimal scheme for advance protection against water hammer should be established. Water hammer conditions of product oil pipelines in the case of unplanned power failure of a pump station were analyzed. An optimization model was established with the objective of maximum throughput and minimum sum of throttling pressure of all regulating valves in the next steady state after water hammer accidents and under corresponding constraint conditions, i.e. no overpressure or vaporization throughout the pipeline. Two different strategies were used for model solution: translating hydraulic gradient line method for the downstream of the accident station through optimization with the objective of minimum outlet pressure of each station and depth-first search method for the upstream of the accident station through optimization of minimum total throttling pressure so as to improve the solving speed. The optimization model was applied in practice under the condition of a product oil pipeline in the case of unplanned power failure of a pump station. The control logic of the transient process in the water hammer accident was established based on the optimization result. Its rationality was verified by simulation software SPS which indicated the rationality and reliability of the optimization model.