Collaborative Planning of Distributed Electric-Hydrogen Energy Storage in Power Systems Considering Balancing Risks in Extreme Scenarios

WANG Hongzhen; QIN Boyu; SU Yiwei; CHEN Peicheng; DING Tao

doi:10.7500/AEPS20260109004

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Collaborative Planning of Distributed Electric-Hydrogen Energy Storage in Power Systems Considering Balancing Risks in Extreme Scenarios

更新时间：2026-09-28

- Collaborative Planning of Distributed Electric-Hydrogen Energy Storage in Power Systems Considering Balancing Risks in Extreme Scenarios
- Automation of Electric Power Systems Pages: 1-17(2026)
- 作者机构：
  
  西安交通大学电气工程学院，陕西省西安市 710049
- 作者简介：
- 基金信息：
  
  National Key R&D Program of China(2024YFB2408400)
- DOI：10.7500/AEPS20260109004
  CLC：
- Received：09 January 2026，
  
  Revised：2026-04-15，
  
  Online First：21 July 2026，
- 稿件说明：
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王宏振,秦博宇,苏乙伟等.考虑极端场景平衡风险的电力系统分布式电氢储能协同规划[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260109004.

WANG Hongzhen,QIN Boyu,SU Yiwei,et al.Collaborative Planning of Distributed Electric-Hydrogen Energy Storage in Power Systems Considering Balancing Risks in Extreme Scenarios[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260109004.
王宏振,秦博宇,苏乙伟等.考虑极端场景平衡风险的电力系统分布式电氢储能协同规划[J/OL].电力系统自动化, http://dx.doi.org/10.7500/AEPS20260109004. DOI：

WANG Hongzhen,QIN Boyu,SU Yiwei,et al.Collaborative Planning of Distributed Electric-Hydrogen Energy Storage in Power Systems Considering Balancing Risks in Extreme Scenarios[J/OL].Automation of Electric Power Systems, http://dx.doi.org/10.7500/AEPS20260109004. DOI：

摘要

电氢储能协同是实现电力系统多时间尺度调节和极端场景电力保障的关键路径。然而，极端场景特征刻画不完整，电氢储能空间配置灵活性挖掘不充分，以及大规模多场景电氢储能协同规划求解困难等问题对电力系统电氢储能的适用性提出了挑战。针对以上问题，文中提出了考虑极端场景平衡风险的电力系统分布式电氢储能协同规划框架：构建了基于气象-源荷多维时间序列信息集和多维时间序列聚类算法的电力系统源荷场景集构建方法；考虑氢储能中制储环节和发电环节异地部署模式，建立了计及极端场景平衡风险的分布式电氢储能协同规划模型；针对非显式、高维决策优化模型，提出了基于树结构帕森估计器的双层序列求解算法。以IEEE RTS-79系统作为验证算例，验证了所提方法的有效性，并以750 kV西北电网作为应用算例，验证了方法在大规模区域电网中的适用性。

Abstract

The collaboration of electric-hydrogen energy storage is a key path to realizing multi-time-scale regulation of power systems and guaranteeing power supply in extreme scenarios. However

problems including incomplete characterization of extreme scenario characteristics

insufficient exploitation of spatial configuration flexibility of electric-hydrogen energy storage

and solving difficulties in large-scale multi-scenario collaborative planning of electric-hydrogen energy storage pose challenges to the applicability of electric-hydrogen energy storage in power systems. To tackle the above problems

this paper proposes a collaborative planning framework for distributed electric-hydrogen energy storage in power systems considering balancing risks in extreme scenarios. A construction method for power system source-load scenario sets is established based on meteorology-source-load multi-dimensional time series information sets and multi-dimensional time series clustering algorithms. Considering the off-site deployment mode of production-storage links and power generation links in the hydrogen energy storage

a collaborative planning model for distributed electric-hydrogen energy storage considering balancing risks in extreme scenarios is established. For implicit high-dimensional decision optimization models

a two-layer sequential solving algorithm based on tree-structured Parzen estimators is proposed. The IEEE RTS-79 system is adopted as a verification case to verify the effectiveness of the proposed method

and the 750 kV Northwest Power Grid in China is taken as an application case to verify its applicability to large-scale regional power grids.

关键词

Keywords

references

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