Intelligent Natural Gas and Hydrogen Pipeline Dispatching Using the Coupled Thermodynamics-Informed Neural Network and Compressor Boolean Neural Network

Natural gas pipelines have attracted increasing attention in the energy industry thanks to current demand for green and advantages of pipeline transportation. A novel deep learning method is proposed this paper, using a coupled network structure incorporating thermodynamics-informed neural compressor Boolean network, incorporate both functions transportation safety check supply predictions. The model uniformed structure, prediction efficiency accuracy are validated by number numerical tests simulating various engineering scenarios, including hydrogen pipelines. trained can provide dispatchers with suggestions about phases existing during as an index showing safety, while effects operation temperature, pressure compositional purity investigated suggest optimized productions.