Evolving ant direction differential evolution for OPF with non-smooth cost functions

In this paper, an effective and reliable algorithm, termed as evolving ant direction differential evolution (EADDE) algorithm, for solving the optimal power flow problem with non-smooth and non-convex generator fuel cost characteristics is presented. In this method, suitable mutation operator for differential evolution (DE) is found by ant colony search. The genetic algorithm evolves the ant colony parameters and the Newton-Raphson method solves the power flow problem. The proposed algorithm has been examined on the standard IEEE 30-bus and IEEE 57-bus systems with three different objective functions. Different cases were considered to investigate the robustness of the proposed method in finding the global solution. The EADDE provides better results compared to classical DE and other methods recently reported in the literature as demonstrated by simulation results.

[1]  Eric Bonabeau,et al.  Evolving Ant Colony Optimization , 1998, Adv. Complex Syst..

[2]  Malabika Basu,et al.  Optimal power flow with FACTS devices using differential evolution , 2008 .

[3]  L. Lakshminarasimman,et al.  Short-term scheduling of hydrothermal power system with cascaded reservoirs by using modified differential evolution , 2006 .

[4]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. II. Newton, linear programming and interior point methods , 1999 .

[5]  Kit Po Wong,et al.  Evolutionary programming based optimal power flow algorithm , 1999 .

[6]  L. Coelho,et al.  Combining of chaotic differential evolution and quadratic programming for economic dispatch optimization with valve-point effect , 2006, IEEE Transactions on Power Systems.

[7]  Ji-Pyng Chiou,et al.  Ant direction hybrid differential evolution for solving large capacitor placement problems , 2004 .

[8]  Samir Sayah,et al.  Modified differential evolution algorithm for optimal power flow with non-smooth cost functions , 2008 .

[9]  R. Mota-Palomino,et al.  Sparse Reactive Power Scheduling by a Penalty Function - Linear Programming Technique , 1986, IEEE Transactions on Power Systems.

[10]  S. Kannan,et al.  Application and comparison of metaheuristic techniques to generation expansion planning problem , 2005, IEEE Transactions on Power Systems.

[11]  Whei-Min Lin,et al.  An Improved Tabu Search for Economic Dispatch with Multiple Minima , 2002, IEEE Power Engineering Review.

[12]  K. Fahd,et al.  Optimal Power Flow Using Tabu Search Algorithm , 2002 .

[13]  Rainer Storn,et al.  Differential Evolution – A Simple and Efficient Heuristic for global Optimization over Continuous Spaces , 1997, J. Glob. Optim..

[14]  Weerakorn Ongsakul,et al.  Optimal power flow with FACTS devices by hybrid TS/SA approach , 2002 .

[15]  R. Storn,et al.  Differential Evolution: A Practical Approach to Global Optimization (Natural Computing Series) , 2005 .

[16]  M Dorigo,et al.  Ant colonies for the travelling salesman problem. , 1997, Bio Systems.

[17]  C.A. Roa-Sepulveda,et al.  A solution to the optimal power flow using simulated annealing , 2001, 2001 IEEE Porto Power Tech Proceedings (Cat. No.01EX502).

[18]  Ieee Report,et al.  Present Practices in the Economic Operation of Power Systems , 1971 .

[19]  P. Kessel,et al.  Estimating the Voltage Stability of a Power System , 1986, IEEE Power Engineering Review.

[20]  R. Yokoyama,et al.  Improved genetic algorithms for optimal power flow under both normal and contingent operation states , 1997 .

[21]  H. Happ,et al.  Quadratically Convergent Optimal Power Flow , 1984, IEEE Transactions on Power Apparatus and Systems.

[22]  Feng-Sheng Wang,et al.  Hybrid method of evolutionary algorithms for static and dynamic optimization problems with application to a fed-batch fermentation process , 1999 .

[23]  L. Lakshminarasimman,et al.  Hydrothermal coordination using modified mixed integer hybrid differential evolution , 2007 .

[24]  Jouni Lampinen,et al.  A Trigonometric Mutation Operation to Differential Evolution , 2003, J. Glob. Optim..

[25]  C. Thitithamrongchai,et al.  Self-adaptive Differential Evolution Based Optimal Power Flow for Units with Non-smooth Fuel Cost Functions , 2007 .

[26]  Ling Wang,et al.  An improved evolutionary programming for optimization , 2002, Proceedings of the 4th World Congress on Intelligent Control and Automation (Cat. No.02EX527).

[27]  C. Su,et al.  Network Reconfiguration of Distribution Systems Using Improved Mixed-Integer Hybrid Differential Evolution , 2002, IEEE Power Engineering Review.

[28]  A. Semlyen,et al.  Hydrothermal Optimal Power Flow Based on a Combined Linear and Nonlinear Programming Methodology , 1989, IEEE Power Engineering Review.

[29]  J.-P. Chiou,et al.  Estimation of Monod model parameters by hybrid differential evolution , 2001 .

[30]  Adam Semlyen,et al.  Hydrothermal optimal power flow based on a combined linear and nonlinear programming methodology , 1989 .

[31]  Corso Elvezia,et al.  Ant colonies for the traveling salesman problem , 1997 .

[32]  Weerakorn Ongsakul,et al.  Optimal Power Flow by Improved Evolutionary Programming , 2006 .

[33]  Kit Po Wong,et al.  Differential Evolution, an Alternative Approach to Evolutionary Algorithm , 2005 .

[34]  W. Tinney,et al.  Optimal Power Flow By Newton Approach , 1984, IEEE Transactions on Power Apparatus and Systems.

[35]  O. Alsac,et al.  Optimal Load Flow with Steady-State Security , 1974 .

[36]  M. A. Abido,et al.  Optimal power flow using particle swarm optimization , 2002 .

[37]  N. Sisworahardjo,et al.  Unit commitment using the ant colony search algorithm , 2002, LESCOPE'02. 2002 Large Engineering Systems Conference on Power Engineering. Conference Proceedings.

[38]  M. A. Abido,et al.  Optimal power flow using differential evolution algorithm , 2009 .

[39]  Ji-Pyng Chiou,et al.  Ant Direction Hybrid Differential Evolution for Solving Economic Dispatch of Power System , 2006, 2006 IEEE International Conference on Systems, Man and Cybernetics.

[40]  S. J. Huang,et al.  Enhancement of Hydroelectric Generation Scheduling Using Ant Colony System-Based Optimization Approaches , 2001, IEEE Power Engineering Review.

[41]  C. Su,et al.  Variable scaling hybrid differential evolution for solving network reconfiguration of distribution systems , 2005 .

[42]  In-Keun Yu,et al.  Application of the ant colony search algorithm to short-term generation scheduling problem of thermal units , 1998, POWERCON '98. 1998 International Conference on Power System Technology. Proceedings (Cat. No.98EX151).

[43]  Marco Dorigo,et al.  An Investigation of some Properties of an "Ant Algorithm" , 1992, PPSN.

[44]  V. Quintana,et al.  Improving an interior-point-based OPF by dynamic adjustments of step sizes and tolerances , 1999 .

[45]  R. Adapa,et al.  A review of selected optimal power flow literature to 1993. I. Nonlinear and quadratic programming approaches , 1999 .