A Flow State Estimation Framework Based on a Novel Natural Gas Pipeline Network Transient Simulation Method

Abstract In recent years, the collaboration between natural gas systems and electricity power systems (EPS) has become increasingly close. The frequent and highly random energy flow conversions pose great challenges to the online flow state estimation of natural gas networks. In response to the issues of poor adaptability under transient flow conditions, difficulty in establishing a comprehensive network model, and high time costs in existing flow state estimation models, this study establishes a novel transient flow simulation model for natural gas pipeline networks (NGPN) based on the Box-Jenkins model. The Box-Jenkins model, known for its computational efficiency in parameter identification of dynamic systems in the field of automatic control, is derived for the first time in this study based on the partial differential equations of natural gas flow. A framework for transient flow state estimation is further established, which enables optimal state estimation at instrumented locations based on Kalman filtering. Additionally, the framework can utilize optimal estimation values to modify the transient flow calculation model based on optimization theory. Through verification with actual natural gas networks and commercial simulation software, the proposed transient flow simulation model for natural gas networks is shown to efficiently achieve flow state observation and model modification.