Optimal Over-Frequency Droop Control for DFIG-Based Wind Farms Under Unreliable Communication

被引:1
作者
Wang, Yaxin [1 ]
Qi, Donglian [2 ]
Zhang, Jianliang [2 ]
Chen, Yulin [3 ]
机构
[1] China Elect Power Res Inst, Beijing 100192, Peoples R China
[2] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Peoples R China
[3] Univ Macau, State Key Lab Internet Things Smart City, Macau, Peoples R China
来源
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS | 2024年 / 10卷 / 06期
基金
中国国家自然科学基金; 国家重点研发计划;
关键词
Rotors; Kinetic energy; Wind speed; Frequency control; Wind farms; Wind energy; Optimization; Game theory; optimal droop control; over-frequency support; unreliable communication; wind power generation; TURBINES;
D O I
10.17775/CSEEJPES.2021.04360
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
Nowadays, high penetration of wind power is integrated into power grids, and WTs usually adopt the MPPT algorithm to maximize power output, which decouples the rotor speeds of wind turbines (WTs) and system frequency. Therefore, WTs cannot provide frequency support like conventional generators. To that end, especially avoiding WTs aggravating excessive power generation during over-frequency events, optimal droop control is proposed to reduce power output by fully utilizing WTs' own potential in accelerating rotors. Due to unreliable communication in a wind farm, a game theory-based distributed rotor kinetic energy optimization model is developed to obtain the ideal WT rotor speed and power reduction. Next, the optimal droop gains for WTs are designed to be proportional to their ideal power reduction. Then, not only the frequency support capability of WTs is fully activated, but also as much wind power as possible will be stored as kinetic energy into the accelerated rotor blades. Finally, the effectiveness and rationality of the proposed control are verified in MATLAB and DIgSILENT.
引用
收藏
页码:2333 / 2340
页数:8
相关论文
共 35 条
[1]  
Arshad M, 2019, INT J GREEN ENERGY, V16, P1073, DOI 10.1080/15435075.2019.1597369
[2]   Enhancing Frequency Response Control by DFIGs in the High Wind Penetrated Power Systems [J].
Chang-Chien, Lee-Ren ;
Lin, Wei-Ting ;
Yin, Yao-Ching .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2011, 26 (02) :710-718
[3]  
Chowdhury B. H., 2008, P 2008 IEEE POW EN S, P1
[4]  
[丁磊 Ding Lei], 2015, [电力系统自动化, Automation of Electric Power Systems], V39, P29
[5]   Innovated Inertia Control of DFIG with Dynamic Rotor Speed Recovery [J].
Lao, Huanjing ;
Zhang, Li ;
Zhao, Tong ;
Zou, Liang .
CSEE JOURNAL OF POWER AND ENERGY SYSTEMS, 2022, 8 (05) :1417-1427
[6]   Releasable Kinetic Energy-Based Inertial Control of a DFIG Wind Power Plant [J].
Lee, Jinsik ;
Muljadi, Eduard ;
Sorensen, Poul ;
Kang, Yong Cheol .
IEEE TRANSACTIONS ON SUSTAINABLE ENERGY, 2016, 7 (01) :279-288
[7]  
Li Heming, 2012, Proceedings of the CSEE, V32, P32
[8]   Decoupling Coupled Constraints Through Utility Design [J].
Li, Na ;
Marden, Jason R. .
IEEE TRANSACTIONS ON AUTOMATIC CONTROL, 2014, 59 (08) :2289-2294
[9]  
Li N, 2012, IEEE DECIS CONTR P, P7764, DOI 10.1109/CDC.2012.6426086
[10]  
Li N, 2011, IEEE DECIS CONTR P, P2434, DOI 10.1109/CDC.2011.6161053