Multi-objective Coordinated Design of TCSC and SVC for improving transient stability

被引:2
作者
Ma Hanyi [1 ]
Du Chen [2 ]
机构
[1] Nanjing Univ Sci & Technol, Coll Automat, Nanjing, Jiangsu, Peoples R China
[2] Fangtian Power Technol Co Ltd, Nanjing, Jiangsu, Peoples R China
来源
2015 FIFTH INTERNATIONAL CONFERENCE ON INSTRUMENTATION AND MEASUREMENT, COMPUTER, COMMUNICATION AND CONTROL (IMCCC) | 2015年
关键词
multi-objective optimisation/coordination; TCSC; SVC; multimachine power system; transient stability;
D O I
10.1109/IMCCC.2015.59
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Owing to contradiction between different control objectives under the combined operating mode of different controllers, the coordination operation problem will be translated into multi-objective optimization problem. This thesis presents a global tuning procedure based on multi-objective self-adaptive evolutionary programming algorithm (MOSAEP) which introduces self-adaptive variation rules. The main objective of this algorithm, by minimizing target functions, is to simultaneously optimize pre-selected parameters of TCSC and SVC in coping with the complex nonlinear nature to maintain the power transmission and improve the voltage stability. A three-machine nine-bus power system equipped with the coordinated designed SVC and TCSC controllers is applied to demonstrate the efficiency and robustness of the tuning procedure presented. Simulation results validate the improvement of transient stability in an optimal and globally coordinated manner compared with separate designed controllers.
引用
收藏
页码:246 / 250
页数:5
相关论文
共 12 条
[1]  
[Anonymous], 2005, EVOLUTIONARY MULTIOB
[2]  
Elmezain M, 2008, INT C PATT RECOG, P424
[3]  
FONSECA CM, 1993, PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON GENETIC ALGORITHMS, P416
[4]  
Irving M, 2009, MODERN POWER SYSTEM
[5]  
Mathur R.M., 2002, THYRISTOR BASED FACT
[6]   Physical programming for preference driven evolutionary multi-objective optimization [J].
Reynoso-Meza, Gilberto ;
Sanchis, Javier ;
Blasco, Xavier ;
Garcia-Nieto, Sergio .
APPLIED SOFT COMPUTING, 2014, 24 :341-362
[7]  
SHI Yan, 2008, RES IMPROVEMENT EVOL
[8]   A Hybrid Multiobjective Evolutionary Algorithm for Multiobjective Optimization Problems [J].
Tang, Lixin ;
Wang, Xianpeng .
IEEE TRANSACTIONS ON EVOLUTIONARY COMPUTATION, 2013, 17 (01) :20-45
[9]  
[于晓辉 Yu Xiaohui], 2006, [计算机工程与应用, Computer Engineering and Application], V42, P69
[10]  
Yu Xiaohui, 2006, COMPUTER ENG APPL, V42, P108