论文标题
使用经济模型预测控制，在供水系统实时操作中最大程度地减少泵送能源成本
Minimizing Pumping Energy Cost in Real-time Operations of Water Distribution Systems using Economic Model Predictive Control
论文作者
论文摘要
优化泵操作是水分配系统（WDS）实时管理（WDS）的一项具有挑战性的任务。通过适当的泵调度，可以大大降低泵送成本。在这项研究中，提出了用于实时管理WDS的新型经济模型预测控制（EMPC）框架。最佳泵操作是根据在退缩时间范围内预测的系统行为选择的，目的是最大程度地减少泵送能源成本。在满足所有必需的水需求时，考虑了随时间变化的电价。该框架的新颖性是选择在每个泵站中运行的泵数量作为决策变量，以优化总泵送能源成本。通过使用整数编程，提出的EMPC应用于Richmond Pruned Network的基准案例研究。实现了用载体液压模拟器进行仿真。此外，对使用拟议EMPC获得的结果与使用触发级别控制获得的结果的比较证明了所提出的EMPC的显着经济益处。
Optimizing pump operations is a challenging task for real-time management of water distribution systems (WDSs). With suitable pump scheduling, pumping costs can be significantly reduced. In this research, a novel economic model predictive control (EMPC) framework for real-time management of WDSs is proposed. Optimal pump operations are selected based on predicted system behavior over a receding time horizon with the aim to minimize the total pumping energy cost. Time-varying electricity tariffs are considered while all the required water demands are satisfied. The novelty of this framework is to choose the number of pumps to operate in each pump station as decision variables in order to optimize the total pumping energy costs. By using integer programming, the proposed EMPC is applied to a benchmark case study, the Richmond Pruned network. The simulation with an EPANET hydraulic simulator is implemented. Moreover, a comparison of the results obtained using the proposed EMPC with those obtained using trigger-level control demonstrates significant economic benefits of the proposed EMPC.
