Economic Load Dispatch with Valve Point Loading Effect and Generator Ramp Rate Limits Constraint using MRPSO

Economic load dispatch is the process of allocating generation among the committed units such that the constraints imposed are satisfied and the fuel cost is minimized. In this work proposed a new Particle swarm optimization with moderate random search. Particle swarm optimization is a population based optimization technique that can be applied to a wide range of engineering problems. Particle swarm optimization with a moderate-random-search strategy called MRPSO, enhances the ability of particles to explore the solution spaces more effectively and increases their convergence rates. In this paper the power and usefulness of the MRPSO algorithm is demonstrated through its application to three and six generator systems with valve point loading effect and ramp rate limit constraints.

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

[2]  K. S. Swarup,et al.  Swarm intelligence approach to the solution of optimal power flow , 2006 .

[3]  ADEL ALI ABOU EL-ELA Optimized Generation Costs Using Modified Particle Swarm Optimization Version , 2008 .

[4]  James A. Momoh,et al.  Improved interior point method for OPF problems , 1999 .

[5]  Chun Che Fung,et al.  Simulated annealing based economic dispatch algorithm , 1993 .

[6]  Jan K. Sykulski,et al.  Application of pattern search method to power system valve-point economic load dispatch , 2007 .

[7]  Lisa L. Grant,et al.  Swarm intelligence and evolutionary approaches for reactive power and voltage control , 2008, 2008 IEEE Swarm Intelligence Symposium.

[8]  C. Sagastizábal,et al.  Solving the unit commitment problem of hydropower plants via Lagrangian Relaxation and Sequential Quadratic Programming , 2005 .

[9]  Tarek Bouktir,et al.  A Genetic Algorithm for Solving the Optimal Power Flow Problem , 2004 .

[10]  Hao Gao,et al.  A New Particle Swarm Algorithm and Its Globally Convergent Modifications , 2011, IEEE Transactions on Systems, Man, and Cybernetics, Part B (Cybernetics).

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

[12]  Isamu Watanabe,et al.  Lagrangian relaxation method for price-based unit commitment problem , 2004 .

[13]  B. Allaoua,et al.  Optimal Power Flow Solution Using Ant Manners for Electrical Network , 2009 .

[14]  D. Ernst,et al.  Transient stability-constrained optimal power flow , 1999, PowerTech Budapest 99. Abstract Records. (Cat. No.99EX376).

[15]  K. C. Almeida,et al.  Short term hydrothermal scheduling with bilateral transactions via bundle method , 2007 .

[16]  Osvaldo R. Saavedra,et al.  EFFICIENT EVOLUTIONARY STRATEGY OPTIMISATION PROCEDURE TO SOLVE THE NONCONVEX ECONOMIC DISPATCH PROBLEM WITH GENERATOR CONSTRAINTS , 2005 .

[17]  Peter B. Luh,et al.  Hydroelectric generation scheduling with an effective differential dynamic programming algorithm , 1990 .