【摘要】 将广义蚁群算法用于电力系统无功优化,建立了相应的的无功优化模型和求解算法,并比较了几种改进方法对优化结果的影响。通过IEEE 6,14,30节点系统仿真计算以及与传统优化方法的比较,表明所提出的方法是有效、可靠的。更多还原

【Abstract】 Generalized ant colony optimization (GACO) is a versatile optimization algorithm, which can be used to solve the discontinuous, nonconvex, and nonlinear constrained optimization problems. It was inspired by the behavior of real ant colonies, in particular, by their foraging behavior. It has the characteristics of positive feedback, distributed computation, and the use of constructive greedy heuristic. The application of GACO to reactive power optimization in electric power systems is investigated. The corresponding mathematical model is established. The solution algorithms are developed. And several refined methods are studied. The presented method has been tested in IEEE 6, 14, 30 bus systems, and the results show that these methods are feasible and efficient.更多还原