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• W4384129402 abstract "Bottom on the ripple of the multiplication of sharing economy, hydrogen energy storage (HES) shared calls for novel solutions to ameliorate the cleanness and economy of micro-grids under the dual carbon target in China. The traditional investment method may become impracticable due to conflicting interests, insufficient utilization, and poor interoperability. The practical and prospective design of HES relies on innovation at the joint investment mechanism under incomplete synchronized and the interested equilibrium under limited rationality. This paper studies the capacity planning method for HES by multiple micro-grids from the sharing perspective. The evolution game model is utilized for conflict of interest, which exactly accounts for limited rationality. The dynamic competitive as well as time-varying demand for HES among multiple micro-grids are established by a small-word complex network theory. The dual dynamic evolutionary game of investment decision in multi-micro-grid and capacity planning for sharing HES is realized by a proposed method of differential evolutionary game algorithm based on experience-weighted attraction learning. The numerical simulation is carried out to verify the effectiveness of the proposed method and interpret the development path for sharing HES. The result shows that, the sizing method with limited rationality reduces the cost by 4.75% compared with the traditional game under complete rationality and 9.15% compared with the multi-objective optimization. The willingness of the park to participate in joint investment in shared HES is influenced by the long-term regulatory demand for energy storage and the decisions of other parks in the neighbors." @default.
• W4384129402 created "2023-07-14" @default.
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• W4384129402 date "2023-09-01" @default.
• W4384129402 modified "2023-10-14" @default.
• W4384129402 title "Sharing hydrogen storage capacity planning for multi-microgrid investors with limited rationality: A differential evolution game approach" @default.
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• W4384129402 doi "https://doi.org/10.1016/j.jclepro.2023.138100" @default.
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