论文部分内容阅读
樊北煤层气因其低压、高密、大起伏、小流量的特征,使得其集输管网系统结构复杂、压力敏感、流动参数变化细微,工艺分析和调度管理工作困难。以PNS(Pipeline Network Simulation)管网仿真软件为核心,结合樊北煤层气集输管网三维地理信息系统、SCADA系统及实时数据库,描述了樊北煤层气集输管网动态仿真调度系统的构架,阐述了动态仿真模型、模型自适应及在线仿真的实现过程,讨论了动态仿真与GIS地理信息系统交互式作用及自动建模和动态查询展示的方法和过程,实现了动态仿真调度系统在线分析和跟踪煤层气管网系统的流动,量化集输管网系统运行状态并分析评价指标,直观搜索、查询及展示系统中各个部分的运行参数,为大型、复杂煤层气地面集输管网系统的调度管理提供及时、准确的分析手段和决策依据,协助调度方案的决策和实施。将系统应用于樊9集气站煤层气集输管网,得到整个管网系统的流动状况,可为调度管理决策提供及时、准确的量化数据。
Due to its characteristics of low pressure, high density, large undulation and small flow rate, Fanbei CBM makes the structure of its gathering and transporting network complicated, sensitive to pressure and slight variation of flow parameters, making it difficult to process analysis and dispatch management. Taking PNS (Pipeline Network Simulation) network simulation software as the core and combining with the three-dimensional geographic information system, SCADA system and real-time database of Fanbei CMG Pipe Network, the architecture of dynamic simulation and scheduling system for Fanbei CBM Pipe Network , Describes the realization process of dynamic simulation model, model adaptation and on-line simulation, and discusses the interaction between dynamic simulation and GIS geographic information system and the method and process of automatic modeling and dynamic query display, and realizes the online analysis of dynamic simulation dispatch system And tracking the flow of coalbed methane pipe network system to quantify the operation status of the gathering pipe network system and analyze the evaluation index to visually search, query and display the operating parameters of each part of the system for the scheduling of large, complex coalbed methane gathering and transportation network system Management to provide timely and accurate analytical tools and decision-making basis to assist in the scheduling decision-making and implementation. The system is applied to the CBM gathering network in Fan 9 gas gathering station to get the flow status of the whole pipe network system and provide timely and accurate quantitative data for the scheduling management decision.