Optimization configuration of hybrid energy storage capacities for large-scale renewable energy bases in desert: A case study of Tennger, China

China is accelerating the development of large-scale renewable energy bases (LREBs) in the northwest desert, requiring ultra-high-voltage transmission to eastern load centers. In this emerging scenario, where renewable energy exceeds 70% and flexibility is insufficient, ensuring the security and stability of power system has become a critical challenge. To address this, this study first proposes a desert LREB model with a hybrid energy storage system (HESS), combining advanced adiabatic compressed air energy storage (AA-CAES) and lithium-ion batteries (LIBs), to enable cross-regional power consumption. A double-layer hybrid energy storage capacity optimization model is then developed. The outer model optimizes the annual transmission schedule to stabilize power output and reduce load fluctuations, using deep learning and K-means clustering to address wind and solar uncertainties. The inner model considers system reliability, investment costs, and renewable energy utilization rates to determine the optimal configuration of the HESS. Using the Tengger desert LREB as a case study, the research compares HESS configurations under different transmission utilization hours. Results show that: (1) increasing transmission hours enhances renewable energy utilization but raises storage costs; (2) at 5500 h, combining AA-CAES and LIBs improves annual transmission reliability from 89.1% to 95.6%; (3) the integration of these systems provides significant economic and environmental benefits. This study contributes to improving renewable energy utilization, reliability, and economic viability of LREBs in desert regions, offering valuable insights for similar projects.