An ADMM-based hierarchical optimal active power control (HOAPC) scheme is proposed for synthetic inertial response of large-scale wind farms. The proposed scheme coordinates the active power outputs of wind turbines (WTs) inside the wind farm during the synthetic inertial response process, aiming to minimize the differences in the rotor speed of the WTs and the wind energy loss caused by the decrease in the rotor speed of the WTs. The optimal control is formulated based on the model predictive control (MPC) according to the local WT wind conditions. A hierarchical solution method based on the alternating direction method of multipliers (ADMM) is developed to solve the MPC-based optimization problem in a fast way without the loss of optimality. With the HOAPC, the wind farm controller guarantees the rotor speed stability of WTs inside the wind farm and reduces the wind energy losses during the synthetic inertial response process. Moreover, the optimization problem is decomposed to several optimization subproblems solved in parallel. As such, the computation burden of the wind farm central controller is significantly reduced, and the protection of the information privacy of the wind farm is improved. A wind farm with 100 WTs was used to validate the proposed HOAPC scheme.

中文翻译：

---

基于乘子交替方向法的风电场综合惯性响应递阶优化控制


针对大型风电场的综合惯性响应，提出了一种基于ADMM的分层最优有功功率控制（HOAPC）方案。该方案在综合惯性响应过程中协调风电场内风力发电机组的有功功率输出，旨在最小化风力发电机组转子转速的差异以及转子转速下降引起的风能损失。 WT 的。根据当地WT风况，基于模型预测控制（MPC）制定最优控制。开发了一种基于乘子交替方向法 (ADMM) 的分层求解方法，可以在不损失最优性的情况下快速求解基于 MPC 的优化问题。通过HOAPC，风电场控制器保证了风电场内风轮转子转速的稳定性，减少了综合惯性响应过程中的风能损失。此外，优化问题被分解为多个并行求解的优化子问题。这样，大大减轻了风电场中央控制器的计算负担，提高了对风电场信息隐私的保护。一个拥有 100 个风轮的风电场被用来验证所提出的 HOAPC 方案。