Distributionally robust optimization of capacity configuration in P2G stations considering the impact of wide power fluctuations

The volatility of renewable energy generation accelerates the aging of water distributionally robust optimization within Power-to-Gas （P2G） stations. Existing optimization models fail to effectively account for the impact of wide power fluctuations on the service life of water electrolysis equipment and the capacity configuration of P2G stations. In this context， this paper proposes a distributionally robust optimization model for the capacity configuration in P2G stations， taking into consideration the service life of electrolysis equipment. Firstly， a model for assessing the degradation of water electrolysis equipment service life is introduced， considering the influence of power fluctuations. Subsequently， an optimization and planning model for an integrated electricity and natural gas system （IENGS） that includes P2G stations is established. This model optimizes the capacity configuration of electrolysis， methanation， and hydrogen storage tanks within the P2G station. Secondly， a fuzzy set of probability distribution for source-load scenarios is constructed based on l1-norm constraints and l∞-norm constraints. The planning model is reformulated as a min-max-min distributionally robust optimization （DRO） model and solve it using a column-and-constraint generation algorithm. Finally， the proposed model and algorithm are validated using test cases. Results demonstrate that the proposed model can more accurately calculate the economic benefits of P2G stations and extend the expected service life of electrolysis equipment.