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Optimal Operation of a Microgrid with Hydrogen Storage Based on Deep Reinforcement Learning


Microgrid with hydrogen storage is an effective way to integrate renewable energy and reduce carbon emissions. This paper proposes an optimal operation method for a microgrid with hydrogen storage. The electrolyzer efficiency characteristic model is established based on the linear interpolation method. The optimal operation model of microgrid is incorporated with the electrolyzer efficiency characteristic model. The sequential decision-making problem of the optimal operation of microgrid is solved by a deep deterministic policy gradient algorithm. Simulation results show that the proposed method can reduce about 5% of the operation cost of the microgrid compared with traditional algorithms and has a certain generalization capability.

Funding source: This research was funded by the Young and Middle-aged Teachers Education Scientific Research Projects of Fujian Province Education Department (No. JAT190043) and Scientific Research Foundation of Fuzhou University (No. 510901).

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