Solution of multiple UPFC placement problems using Gravitational Search Algorithm

Abstract Optimal power flow is one of the key tasks to be performed in the complicated operation and planning of a power system. The Unified Power Flow Controller (UPFC) is a powerful power electronics device capable of providing complex control of power systems. In this paper, Gravitational Search Algorithm (GSA) is applied to solve optimal power flow problem in the presence of multiple UPFC devices. The performance of GSA is compared for accuracy and convergence characteristics with heuristic search techniques like Biogeography-Based Optimization (BBO), Stud Genetic Algorithm (StudGA), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Probability-Based Incremental Learning (PBIL), on the different cases of standard test systems and real life power system. The tabulated results reveal that GSA has a great capability in handling power system planning and operational problems and to provide good quality solution quickly. The effort of optimal placement of multiple UPFC devices in power system cannot be commonly found in technical literature.

[1]  Jianzhong Zhou,et al.  Parameters identification of hydraulic turbine governing system using improved gravitational search algorithm , 2011 .

[2]  S. S. Thakur,et al.  Optimal static state estimation using improved particle swarm optimization and gravitational search algorithm , 2013 .

[3]  José L. Bernal-Agustín,et al.  Optimal parameters of FACTS devices in electric power systems applying evolutionary strategies , 2007 .

[4]  Laszlo Gyugyi,et al.  Unified power-flow control concept for flexible AC transmission systems , 1992 .

[5]  Mohamed Elsaid Elgamal,et al.  Voltage profile enhancement by fuzzy controlled MLI UPFC , 2012 .

[6]  Provas Kumar Roy,et al.  Solution of unit commitment problem using gravitational search algorithm , 2013 .

[7]  Devendra K. Chaturvedi,et al.  Optimal power flow solution using fuzzy evolutionary and swarm optimization , 2013 .

[8]  Shaik Affijulla,et al.  A new intelligence solution for power system economic load dispatch , 2011, 2011 10th International Conference on Environment and Electrical Engineering.

[9]  R. Jabr Optimal Power Flow Using an Extended Conic Quadratic Formulation , 2008, IEEE Transactions on Power Systems.

[10]  Aniruddha Bhattacharya,et al.  Multi-objective economic emission load dispatch solution using gravitational search algorithm and considering wind power penetration , 2013 .

[11]  L. Gyugyi,et al.  The unified power flow controller: a new approach to power transmission control , 1995 .

[12]  Sakti Prasad Ghoshal,et al.  A novel opposition-based gravitational search algorithm for combined economic and emission dispatch problems of power systems , 2012 .

[13]  Dan Simon,et al.  Biogeography-Based Optimization , 2022 .

[14]  G. W. Stagg,et al.  Computer methods in power system analysis , 1968 .

[15]  Narayana Prasad Padhy,et al.  Power flow control and solutions with multiple and multi-type FACTS devices , 2005 .

[16]  Serhat Duman,et al.  Optimal power flow using gravitational search algorithm , 2012 .

[17]  Ahad Kazemi,et al.  Modelling of Optimal Unified Power Flow Controller (OUPFC) for optimal steady-state performance of power systems , 2011 .

[18]  C. Fuerte-Esquivel,et al.  Unified power flow controller: a critical comparison of Newton-Raphson UPFC algorithms in power flow studies , 1997 .

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

[20]  O. Ceylan,et al.  Gravitational search algorithm for post-outage bus voltage magnitude calculations , 2010, 45th International Universities Power Engineering Conference UPEC2010.

[21]  S. Rebennack Handbook of power systems , 2010 .