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Optimal Scheduling of Electricity-Hydrogen Coupling Virtual Power Plant Considering Hydrogen Load Response

Abstract

With the rapid development of hydrogen production by water electrolysis, the coupling between the electricity-hydrogen system has become closer, providing an effective way to consume surplus new energy generation. As a form of centralized management of distributed energy resources, virtual power plants can aggregate the integrated energy production and consumption segments in a certain region and participate in electricity market transactions as a single entity to enhance overall revenue. Based on this, this paper proposes an optimal scheduling model of an electricity-hydrogen coupling virtual power plant (EHC-VPP) considering hydrogen load response, relying on hydrogen to ammonia as a flexibly adjustable load-side resource in the EHC-VPP to enable the VPP to participate in the day-ahead energy market to maximize benefits. In addition, this paper also considers the impact of the carbon emission penalty to practice the green development concept of energy saving and emission reduction. To validate the economy of the proposed optimization scheduling method in this paper, the optimization scheduling results under three different operation scenarios are compared and analyzed. The results show that considering the hydrogen load response and fully exploiting the flexibility resources of the EHC-VPP can further reduce the system operating cost and improve the overall operating efficiency.

Funding source: The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. The author(s) declare that financial support was received for the research, authorship, and/or publication of this article. This study was supported by Guizhou Power Grid Co., Ltd. (No. 0676002023030201XT00001) and the National Natural Science Foundation of China (52307131).
Related subjects: Applications & Pathways
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/content/journal5578
2024-03-07
2024-04-16
http://instance.metastore.ingenta.com/content/journal5578
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