Özet:

In this paper, a simple and reliable approach of non-dominated sorting teaching learning based optimization (NSTLBO) algorithm has been prescribed to determine the optimal solution for multi-objective short-term hydrothermal scheduling (STHTS) problem. The problem has been modelled in the form of multi-objective functions which includes fuel cost, transmission loss and environmental emissions such as NOx, SOx and COx With various constraints of hydrothermal systems. Added to that, the effect of valve-point loading process has also been considered. The interaction of the present NSTLBO algorithm is to decrease the cost of the fuel, transmission losses and different kinds of emissions. By applying this algorithm a set of non-dominated solutions are created. A fuzzy decision making approach has been involved on these solution in order to identify the best comprise solution among the group of solutions. The practicability of the proposed approach has been demonstrated on a sample test system which consists of four hydro and six thermal units. The experimental finding of this method has been compared with that of well established techniques in order to validate the performance of the test results. The results confirm that the NSTLBO approach delivers a reliable solution and competitive performance for solving Multi-objective short-term hydrothermal scheduling (MOSTHTS) problem combined with emission constraints.

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