Optimal Enhancement Control of Static Voltage Stability Margin for AC/DC Power System With Renewables Considering Control Mode Switching of DC Converter Stations

被引:0
作者
Liu, Wanbin [1 ]
Lin, Shunjiang [1 ]
Yang, Yuerong [1 ]
Yang, Ziqing [1 ]
Liu, Mingbo [1 ]
Li, Qifeng [2 ]
机构
[1] South China Univ Technol, Sch Elect Power Engn, Guangzhou 510640, Peoples R China
[2] Univ Cent Florida, Dept Elect & Comp Engn, Orlando, FL 32816 USA
基金
中国国家自然科学基金; 美国国家科学基金会;
关键词
AC/DC power system; control mode switching; improved relaxed LASSO; Karush-Kuhn-Tucker condition; optimal enhancement control; static voltage stability margin; UNCERTAINTY; ALGORITHM; INTERVAL; ENERGY;
D O I
暂无
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
In an AC/DC power system with high penetration of renewable energy stations (RESs), the injected bus power has high random fluctuation, which brings great challenges to ensuring the sufficient static voltage stability margin (SVSM) of the system. In this paper, considering the impact of uncertain RES output and DC converter stations' control mode switching with the load growth, an optimal SVSM enhancement control model for AC/DC power system is proposed. In the model, the SVSM of the system under uncertain RES power is enhanced by regulating the power output and terminal voltage of generators and the parameters of multiple control modes of DC converter stations. By proposing a triangular convex hull relaxation method and using the uncertainty-aware model (UaM) method and the Karush-Kuhn-Tucker condition of inner-layer optimization model, the proposed bi-layer optimal SVSM enhancement control model is transformed into a single-layer nonlinear programming model, which can be directly solved by the CONOPT solver with high efficiency. Case study on the modified 39-bus AC/DC power system demonstrates that the obtained SVSM enhancement control scheme can accurately consider the influence of DC converter stations' control mode switching with the load growth, identify the influence of uncertain injected bus power on the system SVSM, and enhance the SVSM to satisfy the required secure operation level.
引用
收藏
页码:2565 / 2577
页数:13
相关论文
共 32 条
[1]  
[Anonymous], 2019, Standard GB 38755-2019
[2]  
[Anonymous], 2022, MISO Operations Displays
[3]  
[Anonymous], 2022, Odessa Disturbance Report 2022
[4]   CPFLOW - A PRACTICAL TOOL FOR TRACING POWER-SYSTEM STEADY-STATE STATIONARY BEHAVIOR DUE TO LOAD AND GENERATION VARIATIONS [J].
CHIANG, HD ;
FLUECK, AJ ;
SHAH, KS ;
BALU, N .
IEEE TRANSACTIONS ON POWER SYSTEMS, 1995, 10 (02) :623-630
[5]   Improving voltage stability by reactive power reserve management [J].
Dong, F ;
Chowdhury, BH ;
Crow, ML ;
Acar, L .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2005, 20 (01) :338-345
[6]   A Novel Generation Rescheduling Algorithm to Improve Power System Reliability With High Renewable Energy Penetration [J].
Fan, Miao ;
Sun, Kai ;
Lane, Derek ;
Gu, Wei ;
Li, Zhengshuo ;
Zhang, Fang .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2018, 33 (03) :3349-3357
[7]  
Hahn C, 2016, 2016 IEEE/PES TRANSMISSION AND DISTRIBUTION CONFERENCE AND EXPOSITION (T&D)
[8]   A Multi-contingency Preventive Control Method for Static Voltage Stability [J].
Hao, Chen ;
Shi, Yanqiang ;
Shi, Yishan ;
Zhang, Yijing ;
Yi, Zhou ;
Lu, Jianyu ;
Guo, Ruipeng .
2022 4TH INTERNATIONAL CONFERENCE ON SMART POWER & INTERNET ENERGY SYSTEMS, SPIES, 2022, :32-36
[9]   Optimal Operation of Power Systems With Energy Storage Under Uncertainty: A Scenario-Based Method With Strategic Sampling [J].
Hu, Ren ;
Li, Qifeng .
IEEE TRANSACTIONS ON SMART GRID, 2022, 13 (02) :1249-1260
[10]   Ensemble Learning Based Convex Approximation of Three-Phase Power Flow [J].
Hu, Ren ;
Li, Qifeng ;
Qiu, Feng .
IEEE TRANSACTIONS ON POWER SYSTEMS, 2021, 36 (05) :4042-4051