针对弱电网飞轮—电池混合储能难以兼顾频率支撑、设备约束与运行负担的问题，研究分层构网控制方法。利用虚拟同步发电机生成支撑需求，采用递推最小二乘自回归模型对实测净功率失衡进行 0.36 s 在线预测，通过低通滤波与有限候选集经济模型预测控制完成约束功率分配，并开展多工况及 10 kW 开关级缩比仿真。中等扰动下，相较无预测方案，最大频偏和频率绝对偏差积分分别降低 14.56%和 75.64%；10 kW 模型中最大频偏降低 8.22%，未发生硬约束越限；长时运行中频率改善伴随储能通量增加。所提方法可在所测工况下协调预测辅助支撑与设备约束，但预测收益具有工况依赖性，频率性能与储能运行负担之间存在折中。

To address the difficulty of coordinating frequency support, device constraints, and operating burdens in flywheel–battery hybrid energy storage connected to weak grids, a hierarchical grid-forming control method is investigated. A virtual synchronous generator generates the basic support demand. An autoregressive model updated by recursive least squares predicts the measured net power imbalance 0.36 s ahead. Low-pass filtering and finite-candidate-set economic model predictive control perform constrained power allocation. Simulations are conducted under multiple operating conditions, supplemented by a 10-kW switching-level scaled model.Under medium disturbance, the maximum frequency deviation and the integral of absolute frequency deviation are reduced by 14.56% and 75.64%, respectively, compared with the scheme without prediction. In the 10-kW model, the maximum frequency deviation is reduced by 8.22%, with no hard-constraint violations. During long-term operation, improved frequency performance is accompanied by increased storage energy throughput.The proposed method coordinates prediction-assisted frequency support and device constraints under the tested conditions. However, prediction benefits depend on operating conditions, and a trade-off exists between frequency performance and storage operating burdens.