Pipeline Operations Optimization using Data-Driven Model

使用数据驱动模型优化管道运营

• 批准号: 543444-2019
• 负责人: Li, Zukui
• 金额: $ 1.82万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=681042
• 关键词: Pipeline; Operations; Optimization; using; Data

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.

输油管网中泵站的运行能耗巨大。优化泵操作被视为显著节省的主要来源，根据管道的大小，每年可节省数十万美元。威洛格伦系统公司正在开发一个数据驱动的优化系统，通过这个项目的管道操作。所提出的管道操作优化是基于管道系统的数据驱动模型。已从SCADA提取数据，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提高管道运行效率，降低成本。优化还将减少由于泵送操作的巨大电力使用而产生的碳足迹。