Benefit-Based Optimal Allocation of FACTS: SVC Device for Improvement of Transmission Network Loadability

After deregulation, power transactions are significantly increased and thus it becomes more urgent to improve system transmission loadability (TL). Utilization of flexible AC transmission systems (FACTS) can be a better choice to accommodate the requirement instead of building new transmission lines. FACTS devices can enhance system dynamic behavior and system reliability. If they are installed at suitable positions and provide system with sufficient capacities, TL may be largely improved. This issue is playing an increasingly vital role in operation and control for the deregulated markets. The objectives of the optimization problem in the paper involve to maximize the benefit from the future fuel expense with proper investment in the allocation of FACTS devices and to improve TL the most. The solution method proposed is based on the particle swarm optimization (PSO) algorithm involving in the computational procedure of the continuation power flow (PFC). Only static VAR compensator (SVC) is used; however, the installation of SVC and the effectiveness of the solution method can be validated.

[1]  Venkataramana Ajjarapu,et al.  The continuation power flow: a tool for steady state voltage stability analysis , 1991 .

[2]  Barruquer Moner IX. References , 1971 .

[3]  Arturo Roman Messina,et al.  Co-ordinated application of FACTS devices to enhance steady-state voltage stability , 2003 .

[4]  G. Lambert-Torres,et al.  A hybrid particle swarm optimization applied to loss power minimization , 2005, IEEE Transactions on Power Systems.

[5]  Hsiao-Dong Chiang,et al.  CPFLOW: a practical tool for tracing power system steady-state stationary behavior due to load and generation variations , 1995 .

[6]  Georgios C. Stamtsis,et al.  Optimal choice and allocation of FACTS devices in deregulated electricity market using genetic algorithms , 2004, IEEE PES Power Systems Conference and Exposition, 2004..

[7]  T. S. Chung,et al.  A hybrid GA approach for OPF with consideration of FACTS devices , 2000 .

[8]  Weerakorn Ongsakul,et al.  Optimal power flow with multi-type of FACTS devices by hybrid TS/SA approach , 2002, 2002 IEEE International Conference on Industrial Technology, 2002. IEEE ICIT '02..

[9]  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.

[10]  Wei-Jen Lee,et al.  Benefits of FACTS devices for power exchange among Jordanian interconnection with other countries , 2006, 2006 IEEE Power Engineering Society General Meeting.

[11]  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.

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

[13]  G. T. Heydt,et al.  Power Quality Engineering , 2001, IEEE Power Engineering Review.

[14]  V. Vittal,et al.  LP-Based OPF for Corrective FACTS Control to Relieve Overloads and Voltage Violations , 2006, IEEE Transactions on Power Systems.

[15]  K.Y. Lee,et al.  A maximum loading margin method for static voltage stability in power systems , 2006, IEEE Transactions on Power Systems.

[16]  Hany A. Abdelsalam,et al.  Optimal location of the unified power flow controller in electrical power systems , 2004 .

[17]  A. David,et al.  Placement of FACTS devices in open power market , 2000 .

[18]  Allen J. Wood,et al.  Power Generation, Operation, and Control , 1984 .

[19]  Y. Besanger,et al.  A multi-objective genetic algorithm approach to optimal allocation of multi-type FACTS devices for power systems security , 2006, 2006 IEEE Power Engineering Society General Meeting.