Parallel power system restoration planning using heuristic initialization and discrete evolutionary programming

This paper proposes a sectionalizing planning for parallel power system restoration after a complete system blackout. Parallel restoration is conducted in order to reduce the total restoration process time. Physical and operation knowledge of the system, operating personnel experience, and computer simulation are combined in this planning to improve the system restoration and serve as a guidance for system operators/planners. Sectionalizing planning is obtained using discrete evolutionary programming optimization method assisted by heuristic initialization and graph theory approach. Set of transmission lines that should not be restored during parallel restoration process (cut set) is determined in order to sectionalize the system into subsystems or islands. Each island with almost similar restoration time is set as an objective function so as to speed up the resynchronization of the islands. Restoration operation and constraints (black start generator availability, load-generation balance and maintaining acceptable voltage magnitude within each island) is also taken into account in the course of this planning. The method is validated using the IEEE 39-bus and 118-bus system. Promising results in terms of restoration time was compared to other methods reported in the literature.

[1]  Haiping Liang Podjela podsustava za crni start energetskog sustava uzimajući u obzir pouzdanost uspostavljanja , 2015 .

[2]  Takeshi Nagata,et al.  Power system restoration by joint usage of expert system and mathematical programming approach , 1996 .

[3]  W. K. Chen Graph theory and its engineering applications , 1997 .

[4]  Chong Wang,et al.  OBDD-Based Sectionalizing Strategies for Parallel Power System Restoration , 2011, IEEE Transactions on Power Systems.

[5]  Vladimir Terzija,et al.  A graph theory based new approach for power system restoration , 2013, 2013 IEEE Grenoble Conference.

[6]  Mihai Gavrilas,et al.  Heuristic and metaheuristic optimization techniques with application to power systems , 2010 .

[7]  H Afrakhteh,et al.  OPTIMAL ISLANDS DETERMINATION IN POWER SYSTEM RESTORATION , 2009 .

[8]  Vladimir Terzija,et al.  Determination of sectionalising strategies for parallel power system restoration: A spectral clustering-based methodology , 2014 .

[9]  H. Sasaki,et al.  A multi-agent approach to power system restoration , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[10]  R. Kafka,et al.  Power System Restoration - A Task Force Report , 1987, IEEE Transactions on Power Systems.

[11]  H. Mokhlis,et al.  Discrete evolutionary programming to solve network reconfiguration problem , 2013, IEEE 2013 Tencon - Spring.

[12]  Haiping Liang,et al.  SUBSYSTEM PARTITIONING FOR POWER SYSTEM BLACK-START CONSIDERING RESTORATION RELIABILITY , 2015 .

[13]  Vladimir V. Terzija,et al.  A smart power system restoration based on the merger of two different strategies , 2012, 2012 3rd IEEE PES Innovative Smart Grid Technologies Europe (ISGT Europe).

[14]  Newton Bretas,et al.  Node-depth encoding and multiobjective evolutionary algorithm applied to large-scale distribution system reconfiguration , 2011, 2011 IEEE Power and Energy Society General Meeting.

[15]  M. Staropolsky,et al.  Policies for Restoration of a Power System , 1987, IEEE Transactions on Power Systems.

[16]  Vladimir Terzija,et al.  Sectionalising methodology for parallel system restoration based on graph theory , 2015 .

[17]  N. Bretas,et al.  Main chain representation for evolutionary algorithms applied to distribution system reconfiguration , 2005, IEEE Transactions on Power Systems.

[18]  Yan Liu,et al.  Skeleton-Network Reconfiguration Based on Topological Characteristics of Scale-Free Networks and Discrete Particle Swarm Optimization , 2007, IEEE Transactions on Power Systems.

[19]  T. Sakaguchi,et al.  Development of a Knowledge Based System for Power System Restoration , 1983, IEEE Transactions on Power Apparatus and Systems.

[20]  Durlav Hazarika,et al.  Power system restoration: planning and simulation , 2003 .

[21]  Ricardo H. C. Takahashi,et al.  Subpermutation-Based Evolutionary Multiobjective Algorithm for Load Restoration in Power Distribution Networks , 2016, IEEE Transactions on Evolutionary Computation.

[22]  Daniel S. Kirschen,et al.  Guiding a power system restoration with an expert system , 1991 .

[23]  J. Zaborszky,et al.  New Approaches in Power System Restoration , 1992, IEEE Power Engineering Review.

[24]  Amany El-Zonkoly,et al.  Renewable energy sources for complete optimal power system black-start restoration , 2015 .