Journal of South China University of Technology(Natural Science) >

2024 , Vol. 52 >Issue 9: 12 - 23

DOI: https://doi.org/10.12141/j.issn.1000-565X.240123

Energy, Power & Electrical Engineering

Bi-Level Robust Stochastic Optimal Configuration Method for Hydrogen Energy Storage System

  • LIU Mingbo ,
  • ZENG Guihua ,
  • DONG Ping ,
  • LIN Shunjiang
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  • School of Electric Power Engineering，South China University of Technology，Guangzhou 510640，Guangdong，China
刘明波（1964—），男，博士，教授，主要从事电力系统智能调度、电力市场等研究。E-mail： epmbliu@scut.edu.cn

Received date: 2024-03-14

  Online published: 2024-04-07

Supported by

the National Natural Science Foundation of China(52077083)

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Abstract

As a clean, pollution-free secondary energy source with high energy density, hydrogen energy is an ideal energy storage carrier for large-scale consumption of new energy. The electric-heat-hydrogen integrated energy system (EHH-IES), which couples hydrogen energy storage system (HESS) and renewable energy, provides new ideas and solutions for the consumption of new energy. Therefore, this paper focused on how to put in hydrogen energy storage equipment in an economically rational way, and aims to solve the problem of reasonable allocation of hydrogen energy storage equipment capacity and consider the impact of source and load uncertainty on the operation of electrothermal hydrogen integrated energy system. This paper proposed a method for optimizing the capacity of HESS in an EHH-IES considering seasonal storage and source-load uncertainty. Aiming at the relatively large prediction error of wind power and high forecasting accuracy of electric, heat and gas loads at first, the uncertain set and sampling scenario were used to elaborate source and load uncertainty, respectively. Then a bi-level robust stochastic optimization model for configuring hydrogen energy storage considering source-load uncertainty and seasonal storage was constructed, where the upper model optimizes the capacities of devices in hydrogen energy storage with the objective of minimizing total cost of annualized investment costs and operating costs, and the lower model was constructed as a two-stage robust stochastic optimization model to simulate the optimal operation scheme of the EHH-IES under the worst scenario of output wind power in typical days. Since the model is difficult to solve directly, particle swarm optimization and column and constraint generation algorithms were used to solve this type of complex model. Finally, through the analysis of case studies of an EHH-IES, the effectiveness of the proposed method was verified. The obtained solution for the optimal configuration of hydrogen energy storage system can promote the consumption of wind power and improve the economics of the system operation.

Key words： hydrogen energy storage; integrated electric-heat-hydrogen energy system; bi-level robust stochastic optimization; seasonal storage; column and constraints generation algorithm

Cite this article

LIU Mingbo , ZENG Guihua , DONG Ping , LIN Shunjiang . Bi-Level Robust Stochastic Optimal Configuration Method for Hydrogen Energy Storage System[J]. Journal of South China University of Technology(Natural Science), 2024 , 52(9) : 12 -23 . DOI: 10.12141/j.issn.1000-565X.240123

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