A genetic algorithm approach to generator unit commitment

Application of genetic algorithms for the solution of unit commitment with detailed problem formulation, solution methodology and representation is described in this paper. New Encoding and Representation strategy is proposed that can handle large systems with an improvement in solution and faster convergence. The unit commitment problem is formulated as the minimization of the performance index, which is the sum of objectives (fuel cost, startup cost) and constraints (minimum up time (MUT), minimum down time (MDT), spinning reserve). Solution methodology and Simulation Results are provided for a 10-generator unit commitment problem for 24 h duration.