Optimal allocation and energy management of a wind–hydrogen generation system equipped with the speed regulating differential mechanism

What is it about?

The hybrid drive wind turbine (WT) can be friendly connected to the power grid by using a speed regulating differential mechanism (SRDM) instead of partially- or fully-rated converters, which has been considered as a promising solution for the stable consumption of large-scale wind power generation. To further improve the on-grid performance of hybrid drive WTs, this paper develops a multi-source power generation scheme, in which a hydrogen storage system (HSS) is integrated for mitigating the wind power generation intermittencies. The overall architecture and kinematic principles of the proposed wind-hydrogen generation system, called SRDM-based WT with HSS, are firstly analyzed. Then, the graphical descriptions of mathematical models are finalized via the Energetic Macroscopic Representation (EMR) method, by which the physical characteristics and energy flow relationships are revealed. To ensure the economical and stable operation of the proposed wind-hydrogen scheme, an effective optimal allocation framework, considering the uncertainties from wind power output and load demand, is presented to HSS, targeting the maximum annual revenue. The effects of several key HSS parameters on the capacity allocation results are also investigated. Moreover, aiming at the different system working modes, an energy management approach is synthesized to achieve the interaction analysis and power supervision between energy sources and storage elements.

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Photo by Gustavo Quepón on Unsplash

Photo by Gustavo Quepón on Unsplash

Why is it important?

To promote the on-grid performance of VSCF WTs, in our previous publications,33,34 an architecture of the SRDM-based WT with HSS was developed and its numerical modelling and power flow analysis methods were presented. This paper aims to synthesize optimal allocation and energy management of the developed wind-hydrogen system. The contributions are manifested in that, i) the graphical descriptions of system models are realized through the Energetic Macroscopic Representation (EMR) method to reveal the energy flow situations; ii) the optimal allocation of HSS is finalized, considering the uncertainties of wind power output and load demand, by which the system operation economy can be guaranteed; iii) the advanced energy management strategies are investigated to ensure the smooth and stable power supervision between energy sources and storage elements.

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