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Economic Dispatch (ED) is the process of allocating the required load demand between the available generation units such that the cost of operation is minimized. Two Stage Economic dispatch consists of two implementation stages; the first stage involving classic economic power dispatch without considering network loss, where the initial generation plans of the generator units are determined according to the rank of fuel consuming characteristic of the units or the principal of equal incremental rate. The second stage involves economic dispatch considering network loss and security constraints, where two objectives are proposed for the second stage; cost and loss minimization. There have been many algorithms proposed for economic dispatch out of which Differential Evolution is discussed in this paper. Differential Evolution (DE) is a simple and efficient evolutionary algorithm for function optimization over continuous space. The algorithm tries to locate the global optimum solution for the two stage ED problem by iterated refining of the population through reproduction and selection. In this paper, Differential Evolution (DE) technique is presented to solve the two stage economic dispatch problem, which is a non-linear function of generated power as illustrated in fig 2.1. The algorithm is analysed and demonstrated on standard IEEE 14 and 30 bus system consisting of five and six generating units respectively. The minimized cost and loss reduction in the second stage, as compared to the first stage, is illustrated in the analysis. Test results give the first and second stage costs to be $257.5012 and 256.4836 for a demand of 147.10 MW and $434.7735 and $428.5465 respectively for a demand of 259.00 for the 14 Bus case. The rest of the results (including for the 30 Bus case) are contained in tables 4.2, 4.3, 4.4 and 4.5. These results show that the two stage dispatch method can not only reduce the system fuel consumption, but also the system losses.