Value evaluation model study on shared energy storage adapted to the needs of new power system

The global transition in energy structures and the evolution of smart grids have highlighted the critical role of shared energy storage in supporting new power system. However, a systematic framework to evaluate the multidimensional value of shared energy storage remains understudied. To address this gap, this study proposes a comprehensive evaluation methodology for shared energy storage in new power system. Firstly, it analyzes the value emergence mechanism of shared energy storage using the diamond model and investigate its synergistic coupling with new power system. Secondly, it constructs a three-dimensional evaluation indicator system covering value scenarios, value drivers, and value effects. Thirdly, a novel hybrid model integrating kernel principal component analysis (KPCA), dung beetle optimizer (DBO), and least squares support vector machine (LSSVM) is developed to quantify comprehensive value of shared energy storage. KPCA is for feature extraction, DBO is for hyperparameter optimization, and LSSVM is for regression-based value prediction. Case study demonstrates the superior accuracy and robustness of the proposed KPCA-DBO-LSSVM model compared to conventional methods. Key findings reveal that technological innovation capability, tax subsidies, and market supply-demand dynamics are pivotal factors determining value of shared energy storage. This study not only provides a theoretical foundation for shared energy storage value assessment but also offers actionable insights for policymakers and stakeholders to optimize shared energy storage deployment in new power system.