<p>Hydrogen has great potential in reducing carbon emissions due to its high energy density and environmentally friendly properties. As electricity and hydrogen gradually integrate more deeply, this necessitates the gradual improvement of the market mechanisms for the electricity–hydrogen energy market. Thus, this paper proposes a two-layer pricing model for the local energy market that takes into account the dynamic efficiency of electrolyzers. Firstly, based on the dynamic hydrogen production model of electrolyzers, its linearized model is established. Secondly, a local energy market framework, incorporating both electricity and hydrogen, is developed, followed by the establishment of a two-layer pricing model for the local energy market. The upper layer minimizes the service provider’s cost, while the lower layer minimizes the costs for each consumer. Finally, the lower-level model is transformed into constraints using the KKT conditions, and then linearized using a series of methodsThe outcomes reveal that the proposed model generates energy prices that reflect the supply–demand relationship and reduce the costs for system participants.</p>

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Pricing method for local electricity–hydrogen energy market considering the dynamic hydrogen production efficiency of electrolyzers

  • Sumin Guan,
  • Qingping Ye,
  • Lei Wang,
  • Jianchuan Zhu,
  • Hanli Weng,
  • Hong Tan

摘要

Hydrogen has great potential in reducing carbon emissions due to its high energy density and environmentally friendly properties. As electricity and hydrogen gradually integrate more deeply, this necessitates the gradual improvement of the market mechanisms for the electricity–hydrogen energy market. Thus, this paper proposes a two-layer pricing model for the local energy market that takes into account the dynamic efficiency of electrolyzers. Firstly, based on the dynamic hydrogen production model of electrolyzers, its linearized model is established. Secondly, a local energy market framework, incorporating both electricity and hydrogen, is developed, followed by the establishment of a two-layer pricing model for the local energy market. The upper layer minimizes the service provider’s cost, while the lower layer minimizes the costs for each consumer. Finally, the lower-level model is transformed into constraints using the KKT conditions, and then linearized using a series of methodsThe outcomes reveal that the proposed model generates energy prices that reflect the supply–demand relationship and reduce the costs for system participants.