Against the backdrop of global “dual carbon” goals, wind and photovoltaic (PV) energy see growing adoption, but their intermittency threatens grid stability, and energy storage cost complicates optimization. This study proposes a dual-layer optimization model for wind-PV-energy storage systems (WPESS) to cut costs, boost renewable energy absorption, and enhance grid compatibility. The upper layer (capacity configuration) uses differential evolution algorithm to minimize life-cycle cost, optimizing wind, PV, and energy storage capacities, with constraints (e.g., LOLP, curtailment rate) enforced via penalty terms. The lower layer (operation control) optimizes 24 h energy balance, charging/discharging, and grid power purchase to maximize operational economy. Validated with Fujian data (winter, summer, holiday typical days), results show: battery SOC stays 0.2–0.9; curtailment rate and LOLP are extremely low; costs drop by 27.91% (winter), 18.69% (summer), 8.44% (holidays) vs. fixed configuration. This model realizes coordinated optimization, offering references for WPESS application and renewable energy utilization.