A gas pipeline system is in an almost continual state of transition due to changing gas demand. A control method is required to keep a gas pipeline operating in an energy-saving status and provide reliable transmission service for the customers. Model predictive control (MPC) predicts the future states of a system, making it suitable for following gas demand changes. However, to avoid computation time challenges associated with formulating the MPC problem as a large-scale MINLP, an online two-level MPC system is proposed, comprising an upper-level economic MPC (EMPC) and a lower-level tracking MPC (TMPC). EMPC adopts energy cost as the objective function and utilizes a simplified nonlinear model to address long-horizon optimization, while TMPC tracks the status optimized in EMPC, to find the optimal output pressure and the on-off status of the compressors and compressor stations. The performance of the method is demonstrated through application to case studies.

由于天然气需求的变化，天然气管道系统几乎处于持续的过渡状态。需要一种控制方法来使燃气管道保持在节能状态下运行，为客户提供可靠的输送服务。模型预测控制(MPC) 可预测系统的未来状态，使其适合跟踪天然气需求变化。然而，为了避免将 MPC 问题表述为大规模 MINLP 相关的计算时间挑战，提出了一种在线两级 MPC 系统，包括上层经济 MPC（EMPC）和下层跟踪 MPC（TMPC） 。 EMPC以能源成本为目标函数，利用简化的非线性模型进行长期优化，而TMPC跟踪EMPC中的优化状态，找到最佳的输出压力以及压缩机和压缩机站的开关状态。该方法的性能通过案例研究的应用得到证明。