An incorporated algorithm for combined heat and power economic dispatch

Abstract This paper presents an improved genetic algorithm with multiplier updating (IGA_MU) to solve the combined heat and power economic dispatch (CHPED) problem. The improved genetic algorithm (IGA) equipped with an improved evolutionary direction operator (IEDO) and a migration operation can efficiently search and actively explore solutions. The multiplier updating (MU) is introduced to avoid deforming the augmented Lagrange function and resulting in difficulty of solution searching. The proposed approach integrates the IGA and the MU such that it has the merits of automatically adjusting the randomly given penalty to a proper value and requiring only a small-size population for the CHPED problem. Extensive simulations using the proposed method are carried out on various-size systems, and the results are compared with that of the previous methods. Numerical results indicate that the proposed approach has more advantages than other methods in application. Moreover, the proposed algorithm provides an efficacious approach for large-scale systems of the CHPED problem.

[1]  David G. Luenberger,et al.  Linear and nonlinear programming , 1984 .

[2]  Osamu Inoue,et al.  New evolutionary direction operator for genetic algorithms , 1995 .

[3]  Ji-Pyng Chiou,et al.  A hybrid method of differential evolution with application to optimal control problems of a bioprocess system , 1998, 1998 IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence (Cat. No.98TH8360).

[4]  Dag Henning,et al.  Investments in combined heat and power plants: influence of fuel price on cost minimised operation , 2002 .

[5]  H. F. Ravn,et al.  A method to perform probabilistic production simulation involving combined heat and power units , 1996 .

[6]  F. J. Rooijers,et al.  Static economic dispatch for co-generation systems , 1994 .

[7]  A. Ravindran,et al.  Engineering Optimization: Methods and Applications , 2006 .

[8]  Zbigniew Michalewicz,et al.  Evolutionary Algorithms for Constrained Parameter Optimization Problems , 1996, Evolutionary Computation.

[9]  Q. Y. Xuan,et al.  COMBINED HEAT AND POWER ECONOMIC DISPATCH USING GENETIC ALGORITHM BASED PENALTY FUNCTION METHOD , 1998 .

[10]  G. C. Paap,et al.  The influence of voltage sags on the stability of 10 kV distribution networks with large-scale dispersed co-generation and wind generators , 2001 .

[11]  C. S. Chang,et al.  Stochastic multiobjective generation dispatch of combined heat and power systems , 1998 .

[12]  M. J. D. Powell,et al.  Algorithms for nonlinear constraints that use lagrangian functions , 1978, Math. Program..

[13]  Tao Guo,et al.  An algorithm for combined heat and power economic dispatch , 1996 .

[14]  A. Bridgwater,et al.  The influence of feedstock drying on the performance and economics of a biomass gasifier–engine CHP system , 2002 .