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

Optimization is the art of obtaining optimum result under given circumstances. In design, construction and maintenance of any engineering system, engineers have to take many technological and managerial decisions at several stages. The ultimate goal of all such decisions is to either maximize the desired benefit or to minimize the effort or the cost required. This 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 is acting 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 type 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 was considered. Among the four units, the first unit is conventional power unit, second and third units are cogeneration units and the fourth unit is heat only unit. The results obtained by the proposed method are compared with other methods and they clearly demonstrate that the proposed method is practical and valid for real time applications.