Pumped Storage Hydropower(PSH), a pivotal technology for grid-scale energy storage, is increasingly integral to the global low-carbon energy transition. In particular, these stations are essential for facilitating China's strategic objectives of achieving carbon peaking and carbon neutrality. In this paper, we systematically and comprehensively review the application of Hydro-Mechanical-Electrical (HME) Coupled Analysis Method to pumped storage power stations and present a systematic framework. This paper integrates and extends existing research perspectives on coupling mechanisms, modeling methodologies, key applications, and future development directions. We investigate the fundamental interplay between hydraulic, mechanical, and electrical subsystems and conduct a multidimensional comparison of modeling approaches, ranging from traditional centralized parametric models to high-fidelity distributed and hybrid frameworks. Furthermore, we analyze core application areas, including stability assessment, transient process simulation, vibration characteristics, and control strategy optimization. Finally, the study identifies current challenges and emerging trends, such as the integration of digital twin technology, the deployment of large-scale variable speed units, and the advancement of hybrid energy storage systems. Ultimately, it has been pointed out that the future of HME Coupled Analysis Method lies in a shift toward a new paradigm, namely, the integration of physical mechanism models with data-driven artificial intelligence techniques. This is essential for attaining the intelligent operational control and flexible regulation capacity required to maintain stability in power systems characterized by a high penetration of intermittent renewable energy. • A unified “mechanism-modeling-application-trend” framework for HME coupling analysis in pumped storage is established. • Modeling challenges from multi‑time‑scale coupling, nonlinear dynamics, and variable‑speed units are thoroughly analyzed with solutions. • Key applications in stability, transients, vibration control, and operation optimization are comprehensively reviewed. • The digital‑intelligent paradigm shift, integrating AI and digital twins, is identified as the future direction.
Zhang et al. (Thu,) studied this question.