Rapid consumption of fossil fuels is aggravating global environmental pollution

whereas the development scale of renewable energy sources like wind power is expanding. Power-to-hydrogen (P2H) technology

regarded as an effective solution to mitigate renewable curtailment due to the unpredictability of wind and solar generation

holds a crucial role in power systems dominated by these renewable energy sources. Due to the particularity of its working state

the model of P2H device involves many variables and complex constraints

which complicates operation simulation. In this paper

a clustered modeling method based on integer variables is proposed for P2H devices

which reduces the number of variables and improves the solution efficiency. The effectiveness of the clustered model proposed in this paper is verified by the improved IEEE-RTS79 example

and the performance of solutions under different scales and different parameters are compared. This method can accurately simulate the multiple working states of the P2H device

and accelerate the solution process with higher accuracy

which provides a strong support for solving the optimization problems in power systems with large-scale P2H devices.