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Nowadays, the combined offshore wind farm and hydrogen production plant (COWHP) has been installed all around the world and will play an important role in reducing the carbon dioxide emissions. However, the cooperation of the COWHP, the hydrogen pipeline transportation, the power network transmission, and the hydrogen fuel cell electric vehicles (HFCEVs) scheduling is still an essential problem. This problem falls into the category of mixed-integer nonlinear optimization, which involves a significant number of decision variables and constraints. Existing methods have often struggled to effectively solve this problem due to its inherent complexity and non-linear nature. In this paper, a price-guided method is proposed to cooperate with this complex system. First, the COWHP model, the hydrogen pipeline network scheduling model, the power network flow model, the HFCEVs refuelling microgrid model, and the HFCEV traffic flow model in real-world transportation networks are presented. Second, the price-based cooperation model is proposed. Third, price strategies are deployed to cooperate with the complex system. The decision making trial and evaluation laboratory-the technique for order preference by similarity to ideal solution (Dematel-TOPSIS) method is deployed to evaluate the real-time performance of different strategies. The simulation results reveal that in the small vehicle flow transportation network cases, deep deterministic policy gradient (DDPG) has the best real-time evaluation performance; whereas for the large vehicle flow transportation network cases, long short term memory (LSTM) has the best real-time performance. From the posterior evaluation view, LSTM has the best performance for all cases to reduce total operation cost, and also reduce the total waiting time. |
