An Improved Tabu Search for Economic Dispatch with Multiple Minima

This paper develops an improved tabu search algorithm (ITS) for economic dispatch (ED) with noncontinuous and nonsmooth cost functions. ITS employs a flexible memory system to avoid the entrapment in a local minimum, and developed the ideal of "distance" to the fitness to accelerate optimization. The new approach extends simple tabu search algorithm (STS) to real valued optimization problem, and applies parallelism to weaken the dependence of the convergence rate of modified tabu search algorithm (MTS) on the initial condition. Effectiveness of the method was compared with many conventional methods. Results show that the proposed algorithm can provide accurate solutions with reasonable performance, and has a great potential for other applications in the power system.

[1]  Dale Ross,et al.  Dynamic Economic Dispatch of Generation , 1980, IEEE Transactions on Power Apparatus and Systems.

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

[3]  G. L. Viviani,et al.  Hierarchical Economic Dispatch for Piecewise Quadratic Cost Functions , 1984, IEEE Transactions on Power Apparatus and Systems.

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

[5]  Z.-X. Liang,et al.  A zoom feature for a dynamic programming solution to economic dispatch including transmission losses , 1992 .

[6]  Kwang Y. Lee,et al.  Economic load dispatch for piecewise quadratic cost function using Hopfield neural network , 1993 .

[7]  G. Sheblé,et al.  Genetic algorithm solution of economic dispatch with valve point loading , 1993 .

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

[9]  Jacek Klinowski,et al.  Taboo Search: An Approach to the Multiple Minima Problem , 1995, Science.

[10]  Atte Moilanen.  Parameterization of a metapopulation model: an empirical comparison of several different genetic algorithms, simulated annealing and tabu search , 1995, Proceedings of 1995 IEEE International Conference on Evolutionary Computation.

[11]  Hong-Tzer Yang,et al.  Evolutionary programming based economic dispatch for units with non-smooth fuel cost functions , 1996 .

[12]  Yann-Chang Huang,et al.  Solving the capacitor placement problem in a radial distribution system using Tabu Search approach , 1996 .

[13]  Fushuan Wen,et al.  Tabu search approach to alarm processing in power systems , 1997 .

[14]  Loi Lei Lai,et al.  Application of evolutionary programming to reactive power planning-comparison with nonlinear programming approach , 1997 .

[15]  Dervis Karaboga,et al.  Training recurrent neural networks for dynamic system identification using parallel tabu search algorithm , 1997, Proceedings of 12th IEEE International Symposium on Intelligent Control.

[16]  J. Yuryevich,et al.  Evolutionary-programming-based algorithm for environmentally-constrained economic dispatch , 1998 .

[17]  E. Handschin,et al.  Establishing a rule base for a hybrid ES/XPS approach to load management , 1998 .

[18]  June Ho Park,et al.  Adaptive Hopfield neural networks for economic load dispatch , 1998 .

[19]  A. H. Mantawy,et al.  A new genetic-based tabu search algorithm for unit commitment problem , 1999 .