Application of quantum-inspired binary gravitational search algorithm for optimal power quality monitor placement

This paper presents a combinational quantum-inspired binary gravitational search algorithm (QBGSA) for solving the optimal power quality monitor (PQM) placement problem in power systems for voltage sag assessment. In this algorithm, the standard binary gravitational search algorithm is modified by applying the concept and principles of quantum behaviour as to improve the search capability with faster convergence rate. The optimization considers multi objective functions and handles observability constraints determined by the concept of the topological monitor reach area. The overall objective function consists of three functions which are based on the number of required PQM, monitor overlapping index and sag severity index. The proposed QBGSA is applied on the radial 69- bus distribution system and compared with the conventional binary gravitational search algorithm and binary particle swarm optimization and quantum-inspired binary particle swarm optimization techniques.

[1]  Russell C. Eberhart,et al.  A discrete binary version of the particle swarm algorithm , 1997, 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation.

[2]  P.F. Ribeiro,et al.  Transmission systems power quality monitors allocation , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[3]  Jong-Hwan Kim,et al.  Quantum-inspired evolutionary algorithm for a class of combinatorial optimization , 2002, IEEE Trans. Evol. Comput..

[4]  R. Marler,et al.  The weighted sum method for multi-objective optimization: new insights , 2010 .

[5]  Hossein Nezamabadi-pour,et al.  BGSA: binary gravitational search algorithm , 2010, Natural Computing.

[6]  M.M.A. Salama,et al.  Optimum number and location of power quality monitors , 2004, 2004 11th International Conference on Harmonics and Quality of Power (IEEE Cat. No.04EX951).

[7]  M.H.J. Bollen,et al.  An optimal monitoring program for obtaining Voltage sag system indexes , 2006, IEEE Transactions on Power Systems.

[8]  C. F. M. Almeida,et al.  Allocation of Power Quality Monitors by Genetic Algorithms and Fuzzy Sets Theory , 2009, 2009 15th International Conference on Intelligent System Applications to Power Systems.

[9]  Reza Keypour,et al.  A comparative study on performance of metaheuristics optimization methods for optimal var sizing and allocation , 2010, 2010 IEEE Region 8 International Conference on Computational Technologies in Electrical and Electronics Engineering (SIBIRCON).

[10]  J.G. Vlachogiannis,et al.  Quantum-Inspired Evolutionary Algorithm for Real and Reactive Power Dispatch , 2008, IEEE Transactions on Power Systems.

[11]  Hossein Nezamabadi-pour,et al.  GSA: A Gravitational Search Algorithm , 2009, Inf. Sci..

[12]  H. Shareef,et al.  Optimal power quality monitor placement in power systems based on particle swarm optimization and artificial immune system , 2011, 2011 3rd Conference on Data Mining and Optimization (DMO).

[13]  Tony Hey,et al.  Quantum computing: an introduction , 1999 .

[14]  H. Shareef,et al.  Optimal placement of voltage sag monitors based on monitor reach area and sag severity index , 2010, 2010 IEEE Student Conference on Research and Development (SCOReD).

[15]  Jong-Bae Park,et al.  A New Quantum-Inspired Binary PSO: Application to Unit Commitment Problems for Power Systems , 2010, IEEE Transactions on Power Systems.

[16]  N. Rugthaicharoencheep,et al.  Feeder reconfiguration with dispatchable distributed generators in distribution system by tabu search , 2009, 2009 44th International Universities Power Engineering Conference (UPEC).

[17]  E. Farjah,et al.  Optimal placement of monitors in transmission systems using fuzzy boundaries for voltage sag assessment , 2009, 2009 IEEE Bucharest PowerTech.

[18]  Donald E. Grierson,et al.  Comparison among five evolutionary-based optimization algorithms , 2005, Adv. Eng. Informatics.

[19]  D.M. Vilathgamuwa,et al.  Interline dynamic voltage restorer: a novel and economical approach for multiline power quality compensation , 2004, IEEE Transactions on Industry Applications.