Contingency filtering technique for transient stability constrained optimal power flow

被引:9
|
作者
Jiang, Quanyuan [1 ]
Huang, Zhiguang [2 ]
Xu, Kai [1 ]
机构
[1] Zhejiang Univ, Coll Elect Engn, Hangzhou 310027, Zhejiang, Peoples R China
[2] East China Grid Co Iimited, East China Power Dispatch & Control Ctr, Shanghai 200002, Peoples R China
关键词
filtering theory; load flow control; power system transient stability; time-domain analysis; contingency filtering technique; transient stability constrained optimal power flow; TSCOPF; active contingency; critical contingency; time-domain numerical simulations; relative rotor angles; transient generator voltage dips; interior point method; PART-I; ALGORITHM; OPTIMIZATION; SYSTEMS;
D O I
10.1049/iet-gtd.2013.0072
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
Transient stability constrained optimal power flow (TSCOPF) is an important and difficult problem. When multiple contingencies are considered, a reliable contingency filtering technique should be used to reduce the scale of TSCOPF problem. This study brings in the concepts of active contingency and critical contingency, and develops a novel contingency filtering strategy. Based on time-domain numerical simulations, the proposed contingency filtering strategy first screens all the considered contingencies and identifies active contingencies whose severe indices violate the pre-defined threshold of transient stability, then further finds out the critical contingencies in which some generators are most severely disturbed according to the severe indices trajectories. The severe indices can be such as maximal relative rotor angles, maximal transient generator voltage dips and so on. Taking only the critical contingencies into account, the scale of TSCOPF problem is reduced significantly. Interior point method is used to solve the reduced TSCOPF problem. Numerical results on several cases indicate that the proposed contingency filtering technique is reliable and efficient. Compared with the conventional TSCOPF approach, which involves all the contingencies, the proposed contingency filtering strategy possesses overwhelming advantages in CPU time and memory consumption, and is hopeful to solve TSCOPF problems with many contingencies.
引用
收藏
页码:1536 / 1546
页数:11
相关论文
共 50 条
  • [31] Transient stability constrained optimal power flow using particle swarm optimisation
    Mo, N.
    Zou, Z. Y.
    Chan, K. W.
    Pong, T. Y. G.
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2007, 1 (03) : 476 - 483
  • [32] Optimal operation of power systems constrained by transient stability
    Chen, L
    Ono, A
    Tada, Y
    Okamoto, H
    Tanabe, R
    ELECTRICAL ENGINEERING IN JAPAN, 2001, 137 (01) : 17 - 27
  • [33] Contingency constrained optimal power flow solutions in complex network power grids
    Alzalg, Baha
    Anghel, Catalina
    Gan, Wenying
    Huang, Qing
    Rahman, Mustazee
    Shum, Alex
    Wu, Chai Wah
    2012 IEEE INTERNATIONAL SYMPOSIUM ON CIRCUITS AND SYSTEMS (ISCAS 2012), 2012, : 1636 - 1639
  • [34] A contingency filtering, ranking and assessment technique for on-line transient stability studies
    Ruiz-Vega, D
    Ernst, D
    Ferreira, CM
    Pavella, M
    Hirsch, P
    Sobajic, D
    DRPT2000: INTERNATIONAL CONFERENCE ON ELECTRIC UTILITY DEREGULATION AND RESTRUCTURING AND POWER TECHNOLOGIES, PROCEEDINGS, 2000, : 459 - 464
  • [35] Stability-constrained optimal power flow
    Gan, DQ
    Thomas, RJ
    Zimmerman, RD
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2000, 15 (02) : 535 - 540
  • [36] An Automated Transient Stability Constrained Optimal Power Flow Based on Trajectory Sensitivity Analysis
    Tang, Lei
    Sun, Wei
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (01) : 590 - 599
  • [37] Solution techniques for transient stability-constrained optimal power flow - Part I
    Abhyankar, Shrirang
    Geng, Guangchao
    Anitescu, Mihai
    Wang, Xiaoyu
    Dinavahi, Venkata
    IET GENERATION TRANSMISSION & DISTRIBUTION, 2017, 11 (12) : 3177 - 3185
  • [38] Transient Stability Constrained Optimal Power Flow Using Teaching Learning Based Optimization
    Mukherjee, Aparajita
    Paul, Sourav
    Roy, Provas Kumar
    INTERNATIONAL JOURNAL OF ENERGY OPTIMIZATION AND ENGINEERING, 2015, 4 (01) : 18 - 35
  • [39] Parallel Transient Stability-Constrained Optimal Power Flow Using GPU as Coprocessor
    Geng, Guangchao
    Jiang, Quanyuan
    Sun, Youxian
    IEEE TRANSACTIONS ON SMART GRID, 2017, 8 (03) : 1436 - 1445
  • [40] Directional Derivative-Based Transient Stability-Constrained Optimal Power Flow
    Pizano-Martinez, Alejandro
    Fuerte-Esquivel, Claudio R.
    Zamora-Cardenas, Enrique Arnoldo
    Lozano-Garcia, Jose Merced
    IEEE TRANSACTIONS ON POWER SYSTEMS, 2017, 32 (05) : 3415 - 3426