Optimization for DFIG Fast Frequency Response With Small-Signal Stability Constraint

被引:18
作者
Huang, Junkai [1 ]
Yang, Zhifang [1 ]
Yu, Juan [1 ]
Liu, Juelin [1 ]
Xu, Yan [2 ]
Wang, Xuebin [3 ]
机构
[1] Chongqing Univ, Chongqing 400044, Peoples R China
[2] Nanyang Technol Univ, Singapore 639798, Singapore
[3] State Grid Qinghai Elect Power Corp, Elect Power Res Inst, Xining 810001, Qinghai, Peoples R China
基金
国家重点研发计划;
关键词
Frequency control; Doubly fed induction generators; Rotors; Power system stability; Wind turbines; Optimization; Frequency response; Doubly fed induction generator; fast frequency response; parameter design; small-signal rotor angle stability; WIND TURBINE GENERATORS; POWER-SYSTEM; SUPPORT; DESIGN;
D O I
10.1109/TEC.2021.3051944
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The increasing penetration of wind power deteriorates the frequency stability of power systems. To address this issue, a fast frequency response (FFR) from wind farms is required to provide frequency support. However, the power point tracking controllers in wind turbines may counteract the effect of droop-based fast frequency controllers during the frequency response, which makes it difficult to estimate the exact contribution of droop-based fast frequency controllers in wind farms to the system frequency behavior. To address this issue, this article proposes a control parameter design method to fully utilize the frequency support potential of wind turbines. To achieve this goal, an explicit expression for the relationship between the droop-based fast frequency control parameters of the wind turbines and the steady-state frequency deviation is derived. Considering that the fast frequency controller may have a negative effect on the small-signal rotor angle stability, we present a coordinated parameter optimization model of droop-based fast frequency controllers, which improves the system frequency behavior while meeting the small-signal rotor angle stability requirement. A sensitivity-based method is presented to solve the proposed optimization model, which efficiently handles violations of the control parameter constraints. Case studies validate the effectiveness of the proposed method.
引用
收藏
页码:2452 / 2462
页数:11
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