Centrifugal compressor performance prediction and dynamic simulation of natural gas hydrogen blended

Abstract

It is great significant to explore the changes of compressor performance for hydrogen transportation. We found that a Gray-RBF neural network prediction model improved prediction accuracy. The prediction error of the model is 2.34 % by data verification. It was found that the hydrogen blending ratio was increased from 0 % to 30 %, the pipeline transmission power was reduced by 9.3 %. Simultaneously injecting hydrogen to natural gas causes the performance curve of the compressor to shift downwards. The pressure ratio decreases by 18.9 % and shaft power decreases by 28.6 % when the hydrogen blending ratio increases from 0 % to 30 %. The injection of hydrogen to natural gas causes the surge range of the compressor to increase, so the stable range to narrow. In general, this research may provide reference and guidance for the transportation research of hydrogen blended natural gas and compressor operation about gas industry.