Approaches for FACTS optimization problem in power systems

This paper discusses thoroughly about different methods for solution of flexible AC transmission systems (FACTS) optimization problem in power systems. First, it explains the requirements of an ideal solution for FACTS optimization problem, then classifies the methods used by researchers in four main groups as classical methods, technical methods, heuristics and mixed methods, and discusses thoroughly about characteristics, advantages and disadvantages of each group of methods. Finally, some tips are offered for future research on this area.

[1]  Graeme Burt,et al.  Optimal flexible alternative current transmission system device allocation under system fluctuations due to demand and renewable generation , 2010 .

[2]  Deepak Divan,et al.  Optimal placement of Distributed Facts devices in power networks Using Particle Swarm Optimization , 2009, 2009 IEEE Energy Conversion Congress and Exposition.

[3]  M. Kalantar,et al.  A new approach for congestion management via optimal location of FACTS devices in deregulated power systems , 2008, 2008 Third International Conference on Electric Utility Deregulation and Restructuring and Power Technologies.

[4]  U.P. Mhaskar,et al.  Power oscillation damping using FACTS devices: modal controllability, observability in local signals, and location of transfer function zeros , 2006, IEEE Transactions on Power Systems.

[5]  Ivana Kockar,et al.  Phase shifter placement in large-scale systems via mixed integer linear programming , 2003 .

[6]  G. Venayagamoorthy,et al.  Comparison of Enhanced-PSO and Classical Optimization Methods: A Case Study for STATCOM Placement , 2009, International Conference on Intelligent System Applications to Power Systems.

[7]  K Sundareswaran,et al.  Optimal placement of Static VAr Compensators (SVC's) using Particle Swarm Optimization , 2010, 2010 International Conference on Power, Control and Embedded Systems.

[8]  G.B. Gharehpetian,et al.  Power System Security Improvement by Using Differential Evolution Algorithm Based FACTS Allocation , 2008, 2008 Joint International Conference on Power System Technology and IEEE Power India Conference.

[9]  J. Hao,et al.  Optimising location of unified power flow controllers by means of improved evolutionary programming , 2004 .

[10]  Bongkoj Sookananta Determination of FACTS placement using differential evolution technique , 2009, 2009 International Conference on Electrical Engineering and Informatics.

[11]  Zhao Yang Dong,et al.  TCSC allocation based on line flow based equations via mixed-integer programming , 2008, PES 2008.

[12]  P. Renuga,et al.  Bacterial Foraging Algorithm based Enhancement of Voltage Profile and Minimization of Losses Using Thyristor Controlled Series Capacitor (TCSC) , 2010 .

[13]  Seyed Hossein Hosseini,et al.  Allocation of UPFC in North West grid of Iran to increase power system security , 2010, IEEE PES T&D 2010.

[14]  S. Gerbex,et al.  Optimal Location of Multi-Type FACTS Devices in a Power System by Means of Genetic Algorithms , 2001, IEEE Power Engineering Review.

[15]  Ya-Chin Chang,et al.  Transmission System Loadability Enhancement Study by Ordinal Optimization Method , 2011, IEEE Transactions on Power Systems.

[16]  T. K. Saha,et al.  Mixed-integer method for optimal UPFC placement based on line flow-based equations , 2010, 2010 20th Australasian Universities Power Engineering Conference.

[17]  James Kennedy,et al.  Particle swarm optimization , 2002, Proceedings of ICNN'95 - International Conference on Neural Networks.

[18]  A. Yokoyama,et al.  Optimal location of phase shifters in the French network by genetic algorithm , 1999 .

[19]  A.J. Conejo,et al.  Optimal Network Placement of SVC Devices , 2007, IEEE Transactions on Power Systems.

[20]  J. V. Milanovic,et al.  Economic viability of application of FACTS devices for reducing generating costs , 2010, IEEE PES General Meeting.

[21]  P. Venkatesh,et al.  Application of PSO technique for optimal location of FACTS devices considering system loadability and cost of installation , 2005, 2005 International Power Engineering Conference.

[22]  M. Gitizadeh A modified simulated annealing approach to congestion alleviation in a power system using FACTS devices , 2010, 45th International Universities Power Engineering Conference UPEC2010.

[23]  W. F. Long,et al.  Determination of Needed FACTS Controllers That Increase Asset Utilization of Power Systems , 1997 .

[24]  S.N. Singh,et al.  An Approach for Optimal Placement of Static VAr Compensators Based on Reactive Power Spot Price , 2007, IEEE Transactions on Power Systems.

[25]  del Valle,et al.  Optimization of Power System Performance Using Facts Devices , 2010 .

[26]  F. Alvarado,et al.  SVC placement using critical modes of voltage instability , 1993, Conference Proceedings Power Industry Computer Application Conference.

[27]  Azam Karami,et al.  VOLTAGE SECURITY ENHANCEMENT AND CONGESTION MANAGEMENT VIA STATCOM & IPFC USING ARTIFICIAL INTELLIGENCE , 2007 .

[28]  Hiroyuki Mori,et al.  A parallel tabu search based method for determining optimal allocation of FACTS in power systems , 2000, PowerCon 2000. 2000 International Conference on Power System Technology. Proceedings (Cat. No.00EX409).

[29]  A. R. Phadke,et al.  Multi-objective fuzzy-GA formulation for optimal placement and sizing of shunt FACTS controller , 2009, 2009 International Conference on Power Systems.

[30]  A. Kazemi,et al.  Optimal Placement of UPFC in Power Systems Using Genetic Algorithm , 2006, 2006 IEEE International Conference on Industrial Technology.

[31]  Kevin Warwick,et al.  Artificial intelligence techniques in power systems , 1997 .

[32]  Weerakorn Ongsakul,et al.  Optimal placement of multi-type FACTS devices by hybrid TS/SA approach , 2003, Proceedings of the 2003 International Symposium on Circuits and Systems, 2003. ISCAS '03..

[33]  S.J. Cheng,et al.  Optimal Location and Parameter Setting of TCSC by Both Genetic Algorithm and Particle Swarm Optimization , 2007, 2007 2nd IEEE Conference on Industrial Electronics and Applications.

[34]  Fred Glover,et al.  Tabu Search - Part II , 1989, INFORMS J. Comput..

[35]  S. J. Cheng,et al.  Application and comparison of computational intelligence techniques for optimal location and parameter setting of UPFC , 2010, Eng. Appl. Artif. Intell..

[36]  A. Abur,et al.  Static Security Enhancement via Optimal Utilization of Thyristor Controlled Series Capacitors , 2003, IEEE Power Engineering Review.

[37]  S. Jalali,et al.  Determination of location and amount of series compensation to increase power transfer capability , 1998 .

[38]  Muhammad Murtadha Othman,et al.  Thyristor Controlled Series Compensator planning using Evolutionary Programming for transmission loss minimization for system under contingencies , 2010, 2010 IEEE International Conference on Power and Energy.

[39]  B. Vahidi,et al.  Optimal multi-type FACTS allocation using genetic algorithm to improve power system security , 2008, 2008 12th International Middle-East Power System Conference.

[40]  C. Bulac,et al.  Optimal SVC placement in electric power systems using a genetic algorithms based method , 2009, 2009 IEEE Bucharest PowerTech.

[41]  Fred W. Glover,et al.  Tabu Search - Part I , 1989, INFORMS J. Comput..

[42]  Kevin M. Passino,et al.  Biomimicry of bacterial foraging for distributed optimization and control , 2002 .

[43]  Lawrence Jenkins,et al.  Improvement of system security with unified-power- flow controller at suitable locations under network contingencies of interconnected systems , 2005 .

[44]  M. A. Abido,et al.  Optimal location and setting of SVC and TCSC devices using non-dominated sorting particle swarm optimization , 2009 .

[45]  Mahmood Joorabian,et al.  Optimal placement of Multi-type FACTS devices in power systems using evolution strategies , 2011, 2011 5th International Power Engineering and Optimization Conference.

[46]  J. Momoh Electric Power System Applications of Optimization , 2000 .

[47]  S.J. Cheng,et al.  Optimal location and parameters setting of UPFC based on GA and PSO for enhancing power system security under single contingencies , 2008, 2008 IEEE Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century.

[48]  Yue Shi,et al.  A modified particle swarm optimizer , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[49]  Q. Henry Wu,et al.  Bacterial Foraging Algorithm For Dynamic Environments , 2006, 2006 IEEE International Conference on Evolutionary Computation.

[50]  A. R. Phadke,et al.  Multi-objective fuzzy-GA formulation for optimal placement and sizing of shunt FACTS controller , 2009 .

[51]  J. Baskaran,et al.  Optimal location of FACTS devices in a power system solved by a hybrid approach , 2006 .

[52]  N. K. Sharma,et al.  A Novel Placement Strategy for FACTS Controllers , 2002, IEEE Power Engineering Review.

[53]  Ramesh C. Bansal,et al.  International Journal of Emerging Electric Power Systems Optimization Methods for Electric Power Systems : An Overview , 2011 .

[54]  J.R. Cedeno-Maldonado,et al.  Optimal Placement of Facts Controllers in Power Systems via Evolution Strategies , 2006, 2006 IEEE/PES Transmission & Distribution Conference and Exposition: Latin America.

[55]  S.H. Hosseinian,et al.  Optimal placement of multiple STATCOM , 2008, 2008 12th International Middle-East Power System Conference.