Abstract: Independent energy storage in the existing power market faces challenges such as the single-day spot market, limited optimization of real-time market resources, and the single variety of ancillary service market with insufficient compensation. These challenges lead to the inability to fully evaluate and compensate multiple values of energy storage, including rapid frequency regulation, ramping, capacity inertia, and black start. To address this, a multi-stage, multi-market collaborative optimization framework for joint clearing and bidding is proposed. A stochastic optimization model considering risk preference is constructed to enable energy storage to participate in joint bidding for both electricity and multiple ancillary services in the day-ahead market. A real-time rolling optimization strategy based on model predictive control is designed to cope with fluctuations in renewable energy output and load, maximizing arbitrage in the real-time balancing market and compensating for day-ahead deviations. Innovatively, virtual inertia and ramping capability are productized, and their market clearing mechanisms and pricing models are designed. The value of energy storage in these new services is quantified. Finally, a case study based on actual data from a regional power grid verifies that the proposed framework significantly enhances the comprehensive benefits of independent energy storage, demonstrating the positive role of the proposed new ancillary service varieties in system security and economic efficiency. This study provides important theoretical basis and decision support for power market designers and energy storage operators.