With the increasing integration of new energy sources into the power system, their inherent volatility and intermittency have exacerbated the challenges of energy consumption. This study examines source-grid-load-storage systems that incorporate adjustable loads and decentralized energy storage, including distributed new energy, power grids, air conditioners, and electric vehicles. A multi-time-scale collaborative optimization strategy is proposed to enhance the capacity for new energy consumption. The article investigates the response characteristics and consumption potential of flexible resources across different time scales, namely, monthly, day-ahead, and intraday, and develops a multi-objective optimization model aimed at maximizing new energy consumption while minimizing system operating costs. Corresponding collaborative consumption strategies are formulated for each time scale. Specifically, a multi-time-scale source-grid-load-storage collaborative framework that accounts for the flexibility of demand-side management is initially established. Subsequently, a rolling adjustment method based on multi-objective optimization is proposed for monthly, day-ahead, and intraday operations. Finally, the detailed modeling and collaborative utilization of adjustable loads and decentralized energy storage are achieved. Simulation results demonstrate that the proposed strategy reduces the system’s wind and solar curtailment rate to below 3.5%, decreases operating costs by 12.7%, and significantly improves the system’s economic performance and new energy utilization efficiency.