Time-Decoupling Layered Optimization for Energy and Transportation Systems under Dynamic Hydrogen Pricing

The growing popularity of renewable energy and hydrogen-powered vehicles (HVs) will facilitate the coordinated optimization of energy and transportation systems for economic and environmental benefits. However, little research attention has been paid to dynamic hydrogen pricing and its impact on the optimal performance of energy and transportation systems. To reduce the dependency on centralized controllers and protect information privacy, a time-decoupling layered optimization strategy is put forward to realize the low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. First, a dynamic hydrogen pricing mechanism was formulated on the basis of the share of renewable power in the energy supply and introduced into the optimization of distributed energy stations (DESs), which will promote hydrogen production using renewable power and minimize the DES construction and operation cost. On the basis of the dynamic hydrogen price optimized by DESs and the traffic conditions on roads, the raised user-centric routing optimization method can select a minimum cost route for HVs to purchase fuels from a DES with low-cost and/or low-carbon hydrogen. Finally, the effectiveness of the proposed optimization strategy was verified by simulations.

Automated summary

The study proposes a time-decoupling layered optimization strategy to achieve low-carbon and economic operation of energy and transportation systems under dynamic hydrogen pricing. The strategy utilizes a dynamic hydrogen pricing mechanism and user-centric routing optimization method to optimize the performance of distributed energy stations and hydrogen-powered vehicles.