Application meta-heuristics method for short-term unit commitment problem

This work presents a hybrid chaos search genetic algorithm and simulated annealing method (CGA-SA) for solving short-term thermal generating unit commitment (UC) problems. The UC problem involves determining the start-up and shutdown schedules for generating units to meet the forecasted demand at the minimum cost. The commitment schedule must satisfy other constraints such as the generating limits per unit, reserve and individual units. We combined a genetic algorithm with the chaos search. First, it generates a set of feasible unit commitment schedules, and then puts the solution to the SA. The CCA has good global optima search capabilities, but poor local optima search capabilities. The SA method on the other hand, has good local optima search capabilities. Through this combined approach an optimal solution can be found.