Ant colony optimization algorithm with random perturbation behavior to the problem of optimal unit commitment with probabilistic spinning reserve determination

摘要

In this paper, a novel ant colony optimization algorithm with random perturbation behavior (RPACO) based on combination of general ant colony optimization and stochastic mechanism is developed for the solution of optimal unit commitment (UC) with probabilistic spinning reserve determination. In general, the purpose of UC is to enhance the economical efficiency as could as possible while simultaneously satisfying physical and operation constraints of individual unit. Consider the possibility of generating unit failure, the requirement, the sufficient spinning reserve capacity to ensure adequate reliability levels, must be satisfied by the commitment schedule. The security function approach is applied to evaluate the desired level of system security, and the proposed method in this paper, RPACO, is adopted to solve the UC problems. The effectiveness of the proposed method has been demonstrated on the corresponding numerical results. Further, the sensitivity of the desired security level to the optima during optimization is investigated in this paper.