Abstract: Hybrid energy storage systems can capitalize on the diverse advantages of different types of energy storage in terms of both capacity and power. However, in rolling optimization scheduling, electricity energy storage resources（such as battery storage） can be limited in their ability to perform peak shaving and load leveling due to relatively short intra-day rolling time windows. Conversely, power energy storage resources（such as super-capacitor） may have their effectiveness in mitigating wind power fluctuations compromised by longer day-ahead time windows. To address these two issues, this paper presents a day-ahead and intra-day coordinated rolling scheduling strategy that simultaneously considers both electricity and power energy storage resources. First, to address the limited peak-shaving capacity of electricity energy storage, the intra-day rolling period is extended to cover the remaining duration of a day and the scheduling horizon are divided into two parts with different temporal resolutions. This approach encourages the maximum possible involvement of this type of energy storage resource in peak shaving and load leveling while simultaneously improving the model computational efficiency. Then, to address the constraint on power energy storage resources for mitigating fluctuations, a strategy that imposes energy quantity constraints within a finite time window based on statistical analysis of extreme points of fluctuations is proposed. This strategy prevents the resource from depleting its energy reserves due to excessive participation in peak shaving and load leveling. Case studies demonstrate that the scheduling strategy presented in this paper harnesses the scheduling potential of different energy storage resources, achieving peak shaving and load leveling while effectively dampening wind power fluctuations and enhancing wind power accommodation capacity.