Conditional typical scenario-based distributionally robust planning for a WT-PV energy base in the desert involving hydrogen storage introduction

China's desert regions are vast and endowed with excellent wind and solar energy resources, making them ideal areas for the construction of wind turbine (WT)-photovoltaic (PV) energy bases. However, the output peaks of WT and PV occur primarily during midday, leading to a significant temporal and spatial mismatch with the evening peak electricity demand of the receiving utility grid. This mismatch restricts the efficient accommodation of WT and PV output. Furthermore, the volatility and seasonal imbalance of output exacerbate fluctuations in the outgoing power from the base, posing stringent challenges to the stability of inter-regional transmission. To address these issues, this paper proposes the introduction of hydrogen storage technology into desert WT-PV energy bases (called HWP-DEB), leveraging its high energy density and long-term storage capabilities. The integration of hydrogen storage can stabilize outgoing power by enabling temporal and spatial adjustments of WT and PV output. Then, considering the interferences of wind speed and solar irradiation uncertainties, a conditional typical scenario-based distributionally robust planning (CTS-DRP) model is proposed for HWP-DEB, which is an improvement of conventional Wasserstein-based distributionally robust optimization (WDRO). Specifically, by introducing discrete scenarios reflecting prediction errors into the ambiguity set of WDRO and adding constraints on the deviation of non-typical scenarios, the boundary range of all distributions within the ambiguity set is reasonably narrowed. Hence, the accuracy of the ambiguity set can be enhanced, and the conservativeness of WDRO can be reduced. Simulations validate main conclusions: (1) The optimal planning result demonstrates economic sustainability and can ensure the HWP-DEB to achieve seasonal long-term power transfer through hydrogen storage. (2) Compared with conventional WDRP, the proposed CTS-DRP model exhibits lower decision conservatism. This improvement is specifically reflected in a 1.32% reduction in total construction cost, as well as 3.41% and 1.97% increases in the internal rate of return and return on investment, respectively, while still guaranteeing 100% reliable renewable energy delivery.