ePrints

Energy scheduling for integrated electricity–hydrogen systems considering multiphysics dynamics of hybrid water and biomass electrolysis

Lookup NU author(s): Dr Sheng WangORCiD

Downloads

Full text for this publication is not currently held within this repository. Alternative links are provided below where available.

Abstract

© 2025 Elsevier LtdThis paper focuses on the coordinated scheduling problem of integrated electricity–hydrogen systems (IEHS) considering the multiphysics dynamic characteristics of hybrid water and biomass electrolysis. First, a multiphysics-aware hydrogen production model for hybrid water and biomass electrolysis, suitable for the day-ahead or intra-day energy scheduling of IEHS, is presented. The dynamic multiphysics model for alkaline water electrolysis can take advantage of dynamic temperature and hydrogen-to-oxygen impurity crossover processes to optimize the loading range and energy conversion efficiency. The electrochemical model for proton exchange membrane biomass electrolysis can capture operating efficiency and temperature variations to improve the flexibility of hydrogen production. Then, the quasi-steady-state energy scheduling model for IEHS considering the multiphysics dynamics of hybrid water and biomass electrolysis is proposed. A tractable reformulation with multiple convex relaxation techniques, e.g., McCormick envelope, Big-M, outer linear approximation, and binary expansion methods, are utilized to address the highly nonlinear and nonconvex terms arising from the multiphysics-aware electrolysis model and the nonconvex flow quasi-steady-state characteristics of hydrogen network. Numerical results illustrate that the proposed multiphysics-aware electrolysis model can reduce the operating cost by up to 5.74% compared to the constant temperature and constant efficiency model. The solution time is also significantly reduced with a high solution accuracy compared to the original nonconvex and nonlinear model.

Publication metadata

Author(s): Han L, Chen J, Chen A, Gao X, Wang S, Zhai J

Publication type: Article

Publication status: Published

Journal: Renewable Energy

Year: 2025

Volume: 244

Print publication date: 01/05/2025

Online publication date: 14/02/2025

Acceptance date: 06/02/2025

ISSN (print): 0960-1481

ISSN (electronic): 1879-0682

Publisher: Elsevier Ltd

URL: https://doi.org/10.1016/j.renene.2025.122635

DOI: 10.1016/j.renene.2025.122635

Altmetrics

Share