天然气管道网络的数据驱动流量控制:通过异常检测和剩余重量系数进行优化
Wei Chen1, Rui Bian2, Fuxiao Xu2
1Qingdao Huanghai University, Qingdao, Shandong 266555, People's Republic of China.
ACS omega
|September 8, 2025
概括
本研究引入了一种数据驱动的方法,以提高天然气管道流量控制的准确性. 通过检测流动异常和使用残余重量,它可以显著减少分布偏差.
科学领域:
- 能源系统工程 能源系统工程
- 控制理论 控制理论
- 数据科学数据科学数据科学
背景情况:
- 天然气管道网络具有复杂,动态的拓结构和供需关系.
- 当前的控制方法,如不均系数方法,与异常的流量数据作斗争,导致分布不准确和异常.
研究的目的:
- 开发一个高效,准确和快速的智能控制算法,以优化天然气分布网络.
- 通过识别和解决异常流量偏差,提高流量分布的准确性.
主要方法:
- 一种数据驱动的流量控制方法,利用残量系数和流量异常检测.
- 基于数学和统计学意义的剩余重量系数的定义和计算.
- 通过手动干预和自动识别控制模式优化系数设计.
主要成果:
- 拟议的算法通过第四个时间步骤将分布式流与计划对齐.
- 与不均系数方法相比,减少了高达0.69的分布偏差率.
- 提高了跨越不同时间段的计划和实际传输量之间的匹配精度.
结论:
- 数据驱动的流量控制方法确保了天然气网络的精确和快速的分配管理.
- 这种方法为天然气站的智能控制提供了一个基本工具.
- 该方法有效地减轻了由异常流量数据引起的分布异常.
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