Integrating genetic algorithms and tabu search for combined heat and power economic dispatch

The paper presents a new, integrated genetic tabu search algorithm based technique to solve the combined heat and power economic dispatch (CHPED) problem. The proposed method is developed in such a way that a simple GA acts as a base level search. to direct the search towards the optimal region and local searches synergistically combined with tabu search is next employed to fine tune the search to reach the optimal solution. The constraint satisfaction technique has been applied to reduce the computation time and improve the quality of the solution. The proposed method is fast, efficient and applicable to all types of non-linear and discontinuous objective functions. In order to prove the validity and effectiveness of the proposed algorithm, a test system with four units is considered. Among the four units, the first unit is a conventional power unit, the second and third units are cogeneration units and the fourth is a heat only unit. When the results are compared with those of other methods, it is clear that the proposed method is practical and valid for real time applications.