Multistage Distributionally Robust Co-Planning of Power Systems and Electric-Hydrogen Hybrid Charging Stations with Competitive Market Share under Decision-Dependent Uncertainty

The increasing charging demands of electric and hydrogen fuel cell vehicles necessitate the co-planning of power systems and electric-hydrogen Hybrid Charging Stations (HCSs). However, existing planning models are static and lack progressive transformation consideration in vehicle market share evolution, thereby leading to impractical planning decisions that are incompatible with the long-term dynamic transformation. To this end, this paper proposes a multistage decision-dependent distributionally robust co-planning framework for the low-carbon orderly transformation of power and transportation systems. This multistage framework comprehensively encompasses the progressive replacement of traditional gas stations by HCSs, the expansion of corresponding facilities and a detailed operational model to derive a robust, flexible, and economic planning strategy. To describe the phenomena of competition and substitution between different types of vehicles, we develop a novel dynamic vehicle market share model leveraging a three-dimensional competitive Lotka-Volterra equation. Based upon this model, two decision-dependent ambiguity sets are constructed to explicitly capture the endogenous uncertainty in the diffusion of alternative fuel vehicles and reduction in internal combustion vehicles. Subsequently, a nested multistage decision-dependent distributionally robust formulation is established for the coplanning problem of power systems and HCSs. To effectively address the computational challenges for solving the proposed problem, we develop a customized solution algorithm based on the strengthened Benders cut and stochastic dual dynamic integer programming algorithm. Case studies on IEEE 33-bus and IEEE 123-bus systems validate the effectiveness and superiority of the proposed planning framework.