Two-stage controlled islanding strategy based on Stoer-Wagner and improved Dinic algorithms

The controlled islanding for the power system is an effective method to deal with the emergent situations caused by large disturbances. The size of the solution space would increase exponentially as the scale of the power grid increases. The goal of our controlled islanding strategy is to divide the system into several islands quickly. Meanwhile, the generator coherency and the power-flow disruption have to be taken into consideration carefully. This paper proposed a two-stage fast islanding strategy for large power networks, which is on the basis of large power grid graph theories. In the first stage, the Stoer-Wagner algorithm is employed to obtain the grouping cluster of coherent generators in the dynamic undirected liaison graph. In the second stage, the improved Dinic max-flow method is proposed to search the optimal splitting boundary so as to acquire the minimum power flow impact. Our two-stage islanding strategy does not need to reduce the whole power network. Simulations on IEEE 118-bus and 162-bus power systems showed that the proposed strategy can acquire high quality solutions effectively and efficiently.

[1]  V. Vittal,et al.  Self-Healing in Power Systems: An Approach Using Islanding and Rate of Frequency Decline Based Load Shedding , 2002, IEEE Power Engineering Review.

[2]  S. S. Lamba,et al.  Coherency identification by the method of weak coupling , 1985 .

[3]  B. Chaudhuri,et al.  Coherency identification in power systems through principal component analysis , 2005, IEEE Transactions on Power Systems.

[4]  Amany El-Zonkoly,et al.  New algorithm based on CLPSO for controlled islanding of distribution systems , 2013 .

[5]  Ramesh C. Bansal,et al.  A review of key power system stability challenges for large-scale PV integration , 2015 .

[6]  Ma Shiying,et al.  PMU placement based on power system characteristics , 2009, 2009 International Conference on Sustainable Power Generation and Supply.

[7]  Chih-Chun Wang.  Pruning Network Coding Traffic by Network Coding—A New Class of Max-Flow Algorithms , 2010, IEEE Transactions on Information Theory.

[8]  Fushuan Wen,et al.  Discussion on “Two-Step Spectral Clustering Controlled Islanding Algorithm” , 2014 .

[9]  Kai Sun,et al.  Splitting strategies for islanding operation of large-scale power systems using OBDD-based methods , 2003 .

[10]  Feng Yongqing.  Online Operation Risk Assessment for Power System Static Security Considering Secondary Devices Models , 2008 .

[11]  Kai Sun,et al.  Searching for feasible splitting strategies of controlled system islanding , 2006 .

[12]  P. Kokotovic,et al.  Area Decomposition for Electromechanical Models of Power Systems , 1980 .

[13]  V. Vittal,et al.  System islanding using minimal cutsets with minimum net flow , 2004, IEEE PES Power Systems Conference and Exposition, 2004..

[14]  Mechthild Stoer,et al.  A simple min-cut algorithm , 1997, JACM.

[15]  G.T. Heydt,et al.  A Novel Slow Coherency Based Graph Theoretic Islanding Strategy , 2007, 2007 IEEE Power Engineering Society General Meeting.

[16]  Yusuke Kobayashi,et al.  Max-flow min-cut theorem and faster algorithms in a circular disk failure model , 2014, IEEE INFOCOM 2014 - IEEE Conference on Computer Communications.

[17]  Vladimir Terzija,et al.  Constrained spectral clustering-based methodology for intentional controlled islanding of large-scale power systems , 2015 .

[18]  Liming Wang,et al.  Analysis of causes of outdoor insulators damages on HV and UHV transmission lines in China , 2014, 2014 IEEE Electrical Insulation Conference (EIC).

[19]  Vladimir Terzija,et al.  A new controlled islanding algorithm based on spectral clustering , 2011, 2011 4th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT).

[20]  Ni Jingmi.  Adaptive Islanding Control Based on Slow Coherency—Part III:Design of the Practical Scheme , 2014 .

[21]  Bo Wang,et al.  Study on a fast controlled partition scheme based on improved Dinic max-flow strategy , 2015, 2015 IEEE Power & Energy Society General Meeting.

[22]  K. I. M. McKinnon,et al.  Optimization-Based Islanding of Power Networks Using Piecewise Linear AC Power Flow , 2013, IEEE Transactions on Power Systems.

[23]  V. Vittal,et al.  Slow coherency-based islanding , 2004, IEEE Transactions on Power Systems.

[24]  Wenxin Liu,et al.  Slow Coherency and Angle Modulated Particle Swarm Optimization Based Islanding of Large Scale Power Systems , 2007, 2007 International Joint Conference on Neural Networks.

[25]  Mohammad Reza Aghamohammadi,et al.  Intentional islanding using a new algorithm based on ant search mechanism , 2012 .

[26]  Serap A. Savari,et al.  A Max-Flow/Min-Cut Algorithm for Linear Deterministic Relay Networks , 2011, IEEE Transactions on Information Theory.

[27]  Kai Sun,et al.  A study of system splitting strategies for island operation of power system: a two-phase method based on OBDDs , 2003 .

[28]  Joe H. Chow,et al.  Power System Coherency and Model Reduction , 2019, Power System Modeling, Computation, and Control.

[29]  Oliver Kosut.  Max-flow min-cut for power system security index computation , 2014, 2014 IEEE 8th Sensor Array and Multichannel Signal Processing Workshop (SAM).

[30]  Z Q Bo,et al.  A Novel Real-Time Searching Method for Power System Splitting Boundary , 2010, IEEE Transactions on Power Systems.

[31]  Ma Xin.  Graph Partitioning Method Based on Connected Graph Constrained Knapsack Problem , 2012 .

[32]  Kai Sun,et al.  A simulation study of OBDD-based proper splitting strategies for power systems under consideration of transient stability , 2005 .

[33]  V. Terzija,et al.  Two-step spectral clustering controlled islanding algorithm , 2013, 2013 IEEE Power & Energy Society General Meeting.

[34]  Robin Podmore,et al.  Identification of Coherent Generators for Dynamic Equivalents , 1978, IEEE Transactions on Power Apparatus and Systems.

[35]  Joe H. Chow,et al.  Coherency Based Decomposition and Aggregation , 1981 .