基于自适应动能存储方法的大规模风电场两阶段分散式协调减载控制

Abstract This paper presents a two-stage decentralized coordinated deloading control (TDCDC) scheme of large-scale wind farm (WF) based on adaptive kinetic energy storage (KES) method for minimizing the deviations of voltage and frequency by fully utilizing the KES capabilities of wind turbines (WTs). The KES capacity boundary is quantified by analyzing the current feasible region of the converter, which can be adaptively regulated based on the frequency deviation and the available active power capacities of the WTs during the deloading period. The two-stage decentralized controller is designed to achieve a near-global optimal deloading operation performance without any centralized computations and communication. In the first-stage controller, a global voltage optimization problem is formulated based on the gradient projection method to keep the node voltage within the feasible range. The optimal reactive power reference solved by the first-stage controller is given as input to the second-stage controller. In the second-stage controller, the output power and weak magnetic current are optimized to quickly regulate the frequency and node voltage by fully utilizing the maximum KES capability. The robustness of the proposed TDCDC scheme are demonstrated by considering different working conditions. Case studies in MATLAB/Simulink demonstrated the effectiveness and priority of the proposed method compared with other control schemes under different operation conditions.