Modelling of hydrogen blending into the UK natural gas network driven by a solid oxide fuel cell for electricity and district heating system

Samiran Samanta, Dibyendu Roy, Sumit Roy, Andrew Smallbone, Anthony Paul Roskilly

Research output: Contribution to journalArticlepeer-review

8 Citations (Scopus)
19 Downloads (Pure)

Abstract

A thorough investigation of the thermodynamics and economic performance of a cogeneration system based on solid oxide fuel cells that provides heat and power to homes has been carried out in this study. Additionally, different percentages of green hydrogen have been blended with natural gas to examine the techno-economic performance of the suggested cogeneration system. The energy and exergy efficiency of the system rises steadily as the hydrogen blending percentage rises from 0% to 20%, then slightly drops at 50% H2 blending, and then rises steadily again until 100% H2 supply. The system's minimal levelised cost of energy was calculated to be 4.64 £/kWh for 100% H2. Artificial Neural Network (ANN) model was also used to further train a sizable quantity of data that was received from the simulation model. Heat, power, and levelised cost of energy estimates using the ANN model were found to be extremely accurate, with coefficients of determination of 0.99918, 0.99999, and 0.99888, respectively.

Original languageEnglish
Article number129411
JournalFuel
Volume355
Early online date10 Aug 2023
DOIs
Publication statusPublished - 1 Jan 2024
Externally publishedYes

Bibliographical note

Publisher Copyright:
© 2023 The Authors

Keywords

  • Artificial Neural Network
  • Cogeneration
  • District heating
  • Hydrogen economy
  • Solid Oxide Fuel Cell (SOFC)

ASJC Scopus subject areas

  • Chemical Engineering(all)
  • Fuel Technology
  • Energy Engineering and Power Technology
  • Organic Chemistry

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