The rapid development of renewable energy has brought significant challenges to the safe and stable operation of future renewable-dominated energy systems due to the intermittency and variability of renewable energy sources and demand. These challenges increase the system's flexibility needs at different time scales

from short (seconds

minutes) to medium (hours) and long (weeks

months

seasons) term. Power-to-Hydrogen (P2H) equipment can utilize surplus electricity to produce hydrogen

with a portion of the generated hydrogen injected into the natural gas network. This facilitates the long-term generation-demand balance and the coupling and complementarity of heterogeneous energy sources

including electricity

gas

and hydrogen. First

considering the uncertainty of renewables and load demand

typical operation scenarios are generated based on fuzzy local information and the C-means clustering method. Second

an optimization planning model for the siting and sizing of power-to-hydrogen equipment is constructed to minimize the total system cost while accounting for flexibility demand. Then

the nonlinear and nonconvex power-to-hydrogen optimization model is transformed into a mixed-integer second-order cone programming (MISOCP) problem and solved using the Benders-cut algorithm. Finally

case studies are conducted to verify the correctness of the proposed model and solution method.