Implementation of Genetic Algorithm Based Additive and Divisive Clustering Techniques for Unit Commitment

Saving of Fuel Cost can be done through proper commitment of available generating units. This paper presents a novel technique to solve the problem of unit commitment through sorting of units into different clusters based on Genetic Algorithm (GA). This sorting is implemented in order to decrease the overall operating cost and to assure the various constraints that involve minimum up/down. The technique of unit commitment is a significant assignment in the normal working of power systems which can actually be represented as a large scale minimization problem that involves non linear mixed integers. A new technique employing the concept of cluster algorithm called as additive and divisive hierarchical clustering has been used based on the technique of Genetic Algorithm. Proposed methodology involves two individual algorithms. Additive cluster algorithm has been employed while the load is increasing while divisive cluster algorithm has been used when the load is decreasing. The technique that has been developed has been tested on system with generating units in range of 10 to 100 and the superior performance of the technique has been reported through simulation results.