In the quest for sustainable energy solutions, a groundbreaking study led by Zhuoyu Jiang from Three Gorges Electric Energy Co., Ltd., in Wuhan, China, has introduced a novel approach to managing hydrogen refueling stations (HFS). Published in the journal Energies, the research presents a multi-time-scale layered energy management strategy that promises to revolutionize the efficiency and stability of integrated green hydrogen production, storage, and supply systems.
At the heart of this innovation lies a two-layered strategy. The upper layer focuses on an hourly time scale, optimizing the operating power of HFS equipment to minimize daily operating costs. This is achieved through a parameter adaptive particle swarm optimization (PSA-PSO) algorithm, which introduces Gaussian disturbance and adaptively adjusts learning factors, inertia weights, and disturbance step sizes. “This algorithm significantly improves the ability to search for the optimal solution compared to traditional methods,” Jiang explains, highlighting the enhanced efficiency and accuracy of the PSA-PSO approach.
The lower layer operates on a minute-level time scale, addressing the randomness of renewable energy generation and hydrogen load consumption. Here, a stochastic model predictive control (SMPC) algorithm comes into play. By using Latin hypercube sampling (LHS) and simultaneous backward reduction methods, the algorithm generates and reduces scenarios to obtain high-probability random variable scenarios. These are then integrated into the model predictive control to suppress the disturbance of random variables on system operation.
The implications for the energy sector are profound. Traditional hydrogen production methods often result in high carbon emissions, but the integration of renewable energy sources and advanced energy management strategies can drastically reduce these emissions. “The formation of HFSs can meet ports’ demands for the production of hydrogen-powered equipment, significantly contributing to energy saving and emission reduction,” Jiang notes.
The research demonstrates that the proposed energy management strategy has a good control effect in different typical scenarios, as evidenced by real operation data from a HFS in southern China. The PSA-PSO algorithm shows a superior balance between fast convergence speed and optimization effect, reducing daily operation costs by up to 16,460 ¥ and 17,170 ¥ in different scenarios. The SMPC algorithm, meanwhile, significantly reduces the interference of renewable energy and hydrogen load on electrolyzers and the grid, with power fluctuations decreased by up to 17.2% and 15.9%.
This breakthrough could pave the way for more stable and efficient hydrogen refueling stations, crucial for the widespread adoption of hydrogen as a clean energy source. As the energy sector continues to evolve, such innovations will be vital in achieving sustainable and economically viable solutions. The study, published in Energies, underscores the potential of advanced energy management strategies in shaping the future of green hydrogen production and supply.
Looking ahead, Jiang and his team plan to further refine their energy management strategy by establishing a more comprehensive electrolytic cell model. This will consider the deep coupling of energy and material flow, providing a more accurate reflection of the energy changes and material transfer laws under different working conditions. The ultimate goal is to verify these refined strategies using equipment from an actual HFS in Zhoushan Port, Ningbo, Zhejiang Province, China, setting a new benchmark for the industry.
As the energy landscape continues to shift towards sustainability, innovations like these will be instrumental in driving the transition to a greener future. The work of Jiang and his team at Three Gorges Electric Energy Co., Ltd. is a testament to the power of cutting-edge research in transforming the energy sector and paving the way for a more sustainable world.
