Group Search Optimizer for Economic Load Dispatch: an Animal Searching Technique for Power System Optimization

The economic load dispatch (ELD) is the process of allocating the forecasted load demand among the committed generating units in electric power system and its primary objective is to minimize the total cost of generation while honoring the operational constraints of the available generation?s resource. This thesis concerns with the implementation of group search optimizer (GSO) to find the global solution for nonlinear optimization problems while satisfying equality and inequality constraints in the context of time expansive evaluation of functions. GSO technique implements the animal scanning mechanism metamorphically to design optimum searching strategies for solving optimization problems. Group search algorithm employed in this work is population based algorithm, and resource searching process of animals in nature is analogous to the process of seeking optima in a search space. The promising results on the benchmark function show the applicability of the group search optimizer for solving economic load dispatch problem. The validity of the proposed method has been demonstrated for three, four and six generator electrical power system.