A review of battery energy storage peak-shaving dispatch strategies: operational performance and battery degradation

The substantial proportion of renewables connected to the grid and the continuously widening peak-to-valley load difference is the reason for placing significant pressure on peak-shaving in power systems. Battery energy storage systems have become a key enabling technology for peak shaving and valley filling because of their fast response times and flexible deployment. Existing study has concentrated mainly on short-term peak-shaving performance and operational economics. Nevertheless, the interaction among cycle aging, calendar aging, dynamic changes in State of Health (SOH), and dispatch strategies has received insufficient attention. Furthermore, research on degradation models, evaluation metrics and parameter settings lacks consistency. This paper summarizes four mainstream control strategies for peak-shaving dispatch of battery energy storage systems—ranging from threshold control and time-of-use pricing to predictive optimization and intelligent dispatch—and summarizes the evolutionary logic and operational characteristics of each technology. Based on representative studies, this paper carries out a comparative analysis in terms of operational performance and battery degradation. The results show that existing methods have not yet established a consistent evaluation and optimization framework that balances peak-shaving performance, battery lifespan, and full-life-cycle economics. Finally, the paper summarizes current technical challenges and outlines future research directions, including multi-objective coordinated dispatch, the incorporation of aging models, and engineering validation. This paper serves as a reference for the selection and evaluation of different peak-shaving dispatch strategies and provides a theoretical basis for developing energy storage dispatch methods that balance operational benefits, battery lifespan, and economic efficiency.