Pipeline Operations Optimization using Data-Driven Model

在输油管网中运行泵站所需的能源占巨大的能源消耗。优化泵的运行被视为节省大量资金的主要来源，根据管道的大小，每年可能节省数十万美元。Willowglen Systems Inc.正在通过该项目为管道运营开发一种数据驱动的优化系统。所提出的管道运行优化是基于管道系统的数据驱动模型。已经提取了SCADA的数据，并将开发神经网络模型并将其纳入优化框架。管道运行优化系统的成功开发将会提高管道运行的效率，降低成本。优化还将导致减少碳足迹，因为抽水作业耗电量巨大。

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.