基于蚁群算法和内点法的无功优化混合策略

A hybrid strategy based on ACO and IPM for optimal reactive power flow

基于蚁群优化算法与内点法,提出了一种新颖的混合策略来求解电力系统无功优化问题:不考虑无功优化中的离散约束,采用内点法求解得到初始解;根据优化变量的不同性质将无功优化问题分解为离散优化和连续优化2个子问题,并采用蚁群优化算法和内点法交替求解,使两者的优化结果互为基础、相互利用,从而保证了混合策略的整体寻优效率。最后以IEEE 30和IEEE 118节点作为试验系统,与常规的离散优化算法做比较,验证了该算法的正确性和有效性。

By integrating a ant colony optimization algorithm （ACO） with an interior point method （IPM）, a hybrid strategy for the optimal reactive power flow （ORPF） problem is proposed. First, the original ORPF problem is converted to a continuous non-linear programming problem by relaxing the discrete variables, and the initial solution is obtained by the IPM. Then according to the discrete feature of the control variables, the original ORPF problem is decomposed into a continuous optimization sub-problem and a discrete optimization sub-problem, which are solved by IPM and ACO respectively. By solving the two sub-problems alternately, the optimal solution of the ORPF problem can be obtained. IPM and GA take advantage of each other, so that the efficiency of the hybrid strategy is greatly improved. Furthemore, the numerical example of IEEE 30-bus and IEEE 118-bus system is employed to validate correctness and effectiveness of the proposed algorithm, and the result based on this algorithm is compared with that based on conventional discretization algorithm.