唐善华, 杨毅, 张麟, 郭永华, 侯本权, 杨金辉, 于文广. 天然气管网智能调控初探[J]. 油气储运, 2021, 40(9): 991-996, 1026. DOI: 10.6047/j.issn.1000-8241.2021.09.004
引用本文: 唐善华, 杨毅, 张麟, 郭永华, 侯本权, 杨金辉, 于文广. 天然气管网智能调控初探[J]. 油气储运, 2021, 40(9): 991-996, 1026. DOI: 10.6047/j.issn.1000-8241.2021.09.004
TANG Shanhua, YANG Yi, ZHANG Lin, GUO Yonghua, HOU Benquan, YANG Jinhui, YU Wenguang. Preliminary study on intelligent control of natural gas pipeline networks[J]. Oil & Gas Storage and Transportation, 2021, 40(9): 991-996, 1026. DOI: 10.6047/j.issn.1000-8241.2021.09.004
Citation: TANG Shanhua, YANG Yi, ZHANG Lin, GUO Yonghua, HOU Benquan, YANG Jinhui, YU Wenguang. Preliminary study on intelligent control of natural gas pipeline networks[J]. Oil & Gas Storage and Transportation, 2021, 40(9): 991-996, 1026. DOI: 10.6047/j.issn.1000-8241.2021.09.004

天然气管网智能调控初探

Preliminary study on intelligent control of natural gas pipeline networks

  • 摘要: 调控中心作为管网系统的“决策大脑”,是集合大量数据、规则以及专家经验的综合性决策控制中枢,其与以数据驱动为特征的新一代人工智能发展思路和演进方向十分相近。分析了国内外管道公司和电网公司调控业务的智慧化及数字化转型方案,总结了其最新研究成果。结合人工智能技术的最新进展,基于天然气管网调控业务的需求,初步提出了智能调控的基本概念及功能特征,即实现智能感知、预测预警、优化决策、智能控制,最终达到黑屏调控的智能化调控模式;后续设计了智能调控的体系架构,并分析了智能控制层和智能决策层的关键技术及潜在应用场景。研究成果可为后续人工智能在管网调控领域的发展和应用提供参考。

     

    Abstract: As the "decision-making brain" of a pipeline network system, the control centre is a comprehensive decision-making control centre that integrates large amounts of data, rules and expert experience. It is very similar to the development idea and evolution direction of a new generation of artificial intelligence characterized by data driving. Herein, the intelligent and digital transformation plans for the control business of the pipeline companies and the power grid companies at home and abroad were analyzed, and the latest research results were summarized. Then, combined with the latest development of artificial intelligence technology, the basic concepts and functional characteristics of intelligent control were preliminarily put forward based on the demand of natural gas pipeline networks for the control business, namely, to achieve the intelligent perception, prediction and early warning, optimal decision-making, and intelligent control, and ultimately to realize the intelligent control mode based on black screen. Subsequently, the architecture of intelligent control was designed, and the key technologies of the intelligent control layer and the intelligent decision layer, as well as their potential application scenarios, were analyzed. Finally, the research results are expected to provide reference for the development and application of artificial intelligence in the control of pipeline networks in the future.

     

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