Optimization research on energy consumption and carbon emissions in hydrogen-blended natural gas pipeline networks considering compressor performance - A case study of the west-east gas pipeline (line 1)

Abstract

The blending of hydrogen into natural gas can utilize existing natural gas pipeline infrastructure to achieve long-distance, large-scale, and cost-effective hydrogen transportation. However, the introduction of hydrogen poses a series of new technical and safety challenges to the operation of natural gas pipelines. Addressing these issues, this paper focuses on minimizing compressor station energy consumption and carbon emissions as objective functions, conducting a comprehensive analysis of station operation modes. Incorporating the characteristics of the model, the soft frost search strategy, the hard frost penetration mechanism, and the positive greedy selection mechanism are introduced to propose the IRIME algorithm. Comparisons are made with well-performing optimization algorithms using classical test functions to evaluate algorithm performance. To further validate the algorithm's accuracy, the West-East Gas Pipeline (Line 1) is considered, comparing the convergence speed and precision of the IRIME algorithm, leading to its selection for solving the model. Furthermore, consider analyzing the impact of different hydrogen blending ratios on the performance curves and operating points of compressors. Results indicate that compared to conditions without hydrogen blending, the compressor outlet temperature and pressure drop increase for hydrogen blending ratios of 5%, 10%, 15%, and 20%; as the hydrogen blending ratio increases, the efficiency of fuel-driven compressors, efficiency of electrically driven compressors, and average efficiency of compressor units decrease; with an increase in hydrogen blending ratio, carbon emissions from fuel-driven compressors and electric-driven compressors both decrease. In conclusion, with an increasing hydrogen blending ratio, total energy consumption increases by 3.14%, 5.69%, 8.68%, and 10.90%, while total carbon emissions decrease by 2.99%, 5.36%, 8.32%, and 10.68%. These findings provide valuable insights for operational guidance in the field.