Optimum Scheduling of Generators Using Genetic Algorithm

Variation in load demand does not allow a fixed number of generators working in parallel to share the load in proportion to their capacity and therefore lead to an uneconomical operating cost. Presently the economic load dispatch in a group of generators is decided by the criteria of constant derivative state achieved among all the generators in the group of generators. Thus with n-generators operating together the partial derivatives of fuel cost F to the capacity of generator P, should always prevail with equality for each of the generators. Since the derivative approach for economic load dispatch suffers from the draw back of local maxima, the present work has implemented genetic algorithm, which yields global maxima. Also it has been found that the scheduling of generators with regard to its operation on maxima and minima of their capacity in a particular hour over 24 hours is decided by genetic algorithm GA. It is proved that the GA approach for optimum scheduling of generators, Yields a substantial saving / economy in operating cost over the derivative approach. Software has been developed to implement GA for selection of best string. Here the best string refers to the optimum scheduling of generators in a group. Key words