Hydrogen energy storage siting, capacity optimization, and grid planning analysis under the background of large-scale development of renewable energy

With the rapid expansion of renewable energy (RE), the construction of energy storage facilities has become crucial for improving the flexibility of power systems. Hydrogen energy storage (HES), with its superior inter-seasonal regulation capability, plays a vital role in mitigating seasonal fluctuations in RE generation and stabilizing the power grid (PG) operation. This paper addresses key challenges in determining the optimal siting and sizing of HES facilities, as well as in planning the construction sequence of the associated PG infrastructure. The study also examines the impact of HES on the operational characteristics of the PG. The particle swarm optimization algorithm is employed to analyze the optimal siting and sizing of HES, along with the development of the corresponding PG infrastructure. Long-term simulations, covering 8760 h, are performed using the IEEE 30-bus model and a practical case from the Jiangsu distribution network. The findings indicate that HES can be optimally located at nodes that are connected to multiple other nodes. New power line construction primarily focuses on linking HES or generator nodes to load nodes, facilitating efficient power transfer. Subsequent infrastructure development is concentrated between load nodes to enhance regional interconnection and mitigate system instability.

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Publication Details

Journal
Journal of Renewable and Sustainable Energy
Published
2025-01-01
DOI
https://doi.org/10.1063/5.0247942
Citations
2
Primary Topic
Integrated Energy Systems Optimization
Type
article
Field-Weighted Citation Impact
1.46

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article

Hydrogen energy storage siting, capacity optimization, and grid planning analysis under the background of large-scale development of renewable energy

Rongda Zhang, Hongyu Lin, Xiaoli Zhao
2 citations
Journal of Renewable and Sustainable Energy
Integrated Energy Systems Optimization
1.46
article

Hydrogen energy storage siting, capacity optimization, and grid planning analysis under the background of large-scale development of renewable energy

Rongda Zhang, Hongyu Lin, Xiaoli Zhao
article en
2 citations

Abstract

With the rapid expansion of renewable energy (RE), the construction of energy storage facilities has become crucial for improving the flexibility of power systems. Hydrogen energy storage (HES), with its superior inter-seasonal regulation capability, plays a vital role in mitigating seasonal fluctuations in RE generation and stabilizing the power grid (PG) operation. This paper addresses key challenges in determining the optimal siting and sizing of HES facilities, as well as in planning the construction sequence of the associated PG infrastructure. The study also examines the impact of HES on the operational characteristics of the PG. The particle swarm optimization algorithm is employed to analyze the optimal siting and sizing of HES, along with the development of the corresponding PG infrastructure. Long-term simulations, covering 8760 h, are performed using the IEEE 30-bus model and a practical case from the Jiangsu distribution network. The findings indicate that HES can be optimally located at nodes that are connected to multiple other nodes. New power line construction primarily focuses on linking HES or generator nodes to load nodes, facilitating efficient power transfer. Subsequent infrastructure development is concentrated between load nodes to enhance regional interconnection and mitigate system instability.

Journal of Renewable and Sustainable EnergyVol. 17(2)
China University of Petroleum, Beijing (CN), Harbin Institute of Technology (CN)
National Natural Science Foundation of China, National Social Science Fund of China
Openalex Percentile: Top 19%
Integrated Energy Systems Optimization
1.46
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Hydrogen energy storage siting, capacity optimization, and grid planning analysis under the background of large-scale development of renewable energy — Rongda Zhang, Hongyu Lin, et al. · Journal of Renewable and Sustainable Energy (2025) | TGRS Research Map | TGRS