Optimisation and Comprehensive Evaluation of Alternative Energising Paths for Power System Restoration

Power system restoration after a major blackout is a complex process, in which selection of energising paths is a key issue to realize unit and load restoration safely and efficiently. In general, the energising path scheme made beforehand may not be executed successfully due to the possible faults on the related lines under the extreme system condition, so it is necessary to provide alternative path schemes for system restoration. In view of this, the energising path optimisation based on the minimum cost flow model is investigated, then an iterative searching method for alternative path schemes based on mixed integer linear programming is proposed. The iterative method for alternative path schemes could determine more than one scheme with minimal charging reactive power efficiently. In order to make a comprehensive evaluation of the alternative schemes, an evaluation index set is established, and the method based on similarity to ideal grey relational projection is introduced to achieve the final evaluation. The New England 10-unit 39-bus system and the southern Hebei power system of China are employed to demonstrate the effectiveness of the proposed method. The proposed method can provide more efficient and comprehensive decision support for the dispatchers to select reasonable energising paths.

[1]  Ke Hongfa,et al.  Similarity to ideal-based grey relational projection for multiple criteria decision-making , 2009, 2009 IEEE International Conference on Grey Systems and Intelligent Services (GSIS 2009).

[2]  P. Duggan,et al.  Some considerations in the development of restoration plans for electric utilities serving large metropolitan areas , 2006, IEEE Transactions on Power Systems.

[3]  C. Floudas Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications , 1995 .

[4]  Chong Wang,et al.  PTDF-Based Automatic Restoration Path Selection , 2010, IEEE Transactions on Power Systems.

[5]  Dajiang Wang,et al.  Decision‐making optimization of power system extended black‐start coordinating unit restoration with load restoration , 2017 .

[6]  Gerard Ledwich,et al.  Analysis and optimisation of the preferences of decision-makers in black-start group decision-making , 2013 .

[7]  Wei Sun,et al.  Optimal generator start-up strategy for bulk power system restoration , 2012, PES 2012.

[8]  Can Zhang,et al.  Optimal Skeleton-Network Restoration Considering Generator Start-Up Sequence and Load Pickup , 2019, IEEE Transactions on Smart Grid.

[9]  H. Prömel,et al.  The Steiner Tree Problem: A Tour through Graphs, Algorithms, and Complexity , 2002 .

[10]  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.

[11]  M.-S. Tsai,et al.  Operational experience and maintenance of an on-line expert system for customer restoration and fault testing , 1991 .

[12]  Laurence A. Wolsey,et al.  A branch-and-cut algorithm for the single-commodity, uncapacitated, fixed-charge network flow problem , 2003, Networks.

[13]  Min Yong,et al.  Optimal algorithm for system reconstruction , 2002, Proceedings. International Conference on Power System Technology.

[14]  Dong Zhao-yang Intelligent Optimization Strategy of the Power Grid Reconfiguration During Power System Restoration , 2009 .

[15]  J. J. Ancona A framework for power system restoration following a major power failure , 1995 .

[16]  Pei Zhang,et al.  Computation of Milestones for Decision Support During System Restoration , 2011, IEEE Transactions on Power Systems.

[17]  Vladimir Terzija,et al.  Coordinating self-healing control of bulk power transmission system based on a hierarchical top-down strategy , 2017 .

[18]  S. L. Muchlinski,et al.  Operational experience and maintenance of an on-line expert system for customer restoration and fault testing , 1991, [Proceedings] Conference Papers 1991 Power Industry Computer Application Conference.

[19]  Yutian Liu,et al.  Group decision support system for backbone-network reconfiguration , 2015 .

[20]  Xueping Gu,et al.  Optimisation of network reconfiguration based on a two-layer unit-restarting framework for power system restoration , 2012 .

[21]  M. M. Adibi,et al.  Expert system requirements for power system restoration , 1994 .

[22]  Yutian Liu,et al.  Power system restoration: a literature review from 2006 to 2016 , 2016 .

[23]  Srdjan Dimitrijevic,et al.  An innovative approach for solving the restoration problem in distribution networks , 2011 .

[24]  Sijie Chen,et al.  Blackstart capability planning for power system restoration , 2017 .

[25]  Chen-Ching Liu,et al.  From generic restoration actions to specific restoration strategies , 1995 .

[26]  Wei Sun,et al.  Optimal transmission path search in power system restoration , 2013, 2013 IREP Symposium Bulk Power System Dynamics and Control - IX Optimization, Security and Control of the Emerging Power Grid.

[27]  M. M. Adibi,et al.  Energizing high and extra-high voltage lines during restoration , 1999 .

[28]  Jian Ma,et al.  A subjective and objective integrated approach to determine attribute weights , 1999, Eur. J. Oper. Res..

[29]  LiBao Shi,et al.  Determination of Weight Coefficient for Power System Restoration , 2012, IEEE Transactions on Power Systems.

[30]  Richard E. Rosenthal,et al.  GAMS -- A User's Guide , 2004 .

[31]  Can Zhang,et al.  Network partitioning strategy for parallel power system restoration , 2016 .

[32]  Qiuwei Wu,et al.  Orthogonal genetic algorithm based power system restoration path optimization , 2018, International Transactions on Electrical Energy Systems.

[33]  Cong Sun,et al.  Optimisation for unit restarting sequence considering decreasing trend of unit start-up efficiency after a power system blackout , 2016 .

[34]  Wei Shen,et al.  Development of an interactive rule-based system for bulk power system restoration , 2000 .

[35]  M. Ferris,et al.  Optimal Transmission Switching , 2008, IEEE Transactions on Power Systems.

[36]  Can Zhang,et al.  Two-stage power network reconfiguration strategy considering node importance and restored generation capacity , 2013 .

[37]  Fushuan Wen,et al.  A Restorative Self-Healing Algorithm for Transmission Systems Based on Complex Network Theory , 2016, IEEE Transactions on Smart Grid.