Multi-time scale optimal configuration of user-side energy storage considering demand perception

The promotion of user-side energy storage is a pivotal initiative aimed at enhancing the integration capacity of renewable energy sources within modern power systems. However, there is a notable absence of systematic research exploring the optimal configuration of energy storage tailored to diverse user needs and scenarios. In this study, a multi-time scale optimal configuration approach for user-side energy storage is introduced, which takes into account demand perception. Initially, the behavioral patterns of large-scale electricity consumers are deeply studied, and the discriminant index system for user-side energy storage configurations is established, leveraging the interrelationships among various indicators to discern demand patterns. Subsequently, the uncertainties across multiple time scales are combined and the full lifecycle operational scenarios are captured through clustering techniques. By integrating various profit models, including peak-valley arbitrage, demand response, and demand management, the goal is to optimize economic efficiency throughout the system's lifespan. Consequently, a multi-time scale user-side energy storage optimization configuration model that considers demand perception is constructed. This framework enables a comparative analysis of energy storage capacity allocation across different users, assessing its economic impact, and thus promoting the commercialization of user-side energy storage.