Pipeline Operations Optimization using Data-Driven Model

输油管泵站的运行能耗巨大。根据管道的大小，优化泵的操作被认为是节省大量成本的主要来源，每年可节省数十万美元。Willowglen系统公司正在通过该项目开发一种数据驱动的管道操作优化系统。提出的管道运行优化是基于管道系统的数据驱动模型。从SCADA中提取数据，并将开发神经网络模型并将其纳入优化框架。管道作业优化系统的成功开发将提高管道作业效率，降低成本。由于泵送作业的大量电力消耗，这种优化还将减少碳足迹。

The energy required to operate pump stations in oil pipeline networks accounts for enormous energy consumption. Optimizing pump operations is seen as a major source of significant savings which may be in the range of hundreds of thousands of dollars annually depending on the size of the pipeline. Willowglen Systems Inc. is developing a data-driven optimization system for pipeline operations through this project. The proposed pipeline operations optimization is based on a data-driven model of the pipeline system. Data from SCADA has been extracted and the neural network model will be developed and incorporated into an optimization framework. The successful development of pipeline operations optimization system will improve the efficiency of pipeline operations and reduce the costs. The optimization will also lead to the reduction of the carbon footprint due to the enormous electricity usage of pumping operations.