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Utilizing renewable energy sources such as wind and photovoltaic to identify cost-effective decarbonization pathways for coastal receiving-end power systems is one of the core challenges in achieving the goals of'carbon emission peak and carbon neutrality'of China. By analyzing the techno-economic differences between hydrogen-ammonia storage and existing energy storage technologies (such as electrochemical and compressed air energy storage), a multi-year expansion planning model for power systems incorporating cofiring coupled hydrogen-ammonia energy storage under temporal decarbonization constraints is established, and the techno-economic feasibility of achieving low-cost decarbonization within the power system is explored. The actual data are selected from Guangdong power grid of China for case study. The results demonstrate that, under increasingly stringent carbon reduction constraints, it is necessary to progressively achieve decarbonization targets through technical pathways, such as the newly added wind and photovoltaic storage, the transition from coal to gas in thermal power planning modes, and the newly added hydrogen-ammonia energy storage (including hydrogen cofiring in gas turbines, ammonia cofiring in coal-fired plants, and ammonia decomposition). Compared with a decarbonization mode relying solely on lithium-ion battery peak shaving, the introduction of cofiring coupled hydrogen-ammonia energy storage technology can avoid overloading excessive wind and photovoltaic storage capacity, thus significantly reducing the wind and photovoltaic curtailment rates. This approach not only achieves intensive resource utilization, but also further reduces the decarbonization cost of hydrogen-ammonia energy storage through the reuse of existing thermal power generation infrastructure. Therefore, the use of hydrogen-ammonia energy storage technology for power system decarbonization presents a scalable and economically feasible decarbonization pathway. © 2025 Automation of Electric Power Systems Press. All rights reserved.
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电力系统自动化
ISSN: 1000-1026
Year: 2025
Issue: 5
Volume: 49
Page: 57-68
Cited Count:
SCOPUS Cited Count: 1
ESI Highly Cited Papers on the List: 0 Unfold All
WanFang Cited Count:
Chinese Cited Count:
30 Days PV: 2
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