基于克隆算法的舰船电力系统故障恢复

Shipboard Power System Service Restoration Based on Clonal Algorithm

为了解决舰船电力系统的故障恢复问题,在综合考虑多电站环形供电网络的拓扑结构、发电机的容量限制、负载的优先级以及最大限度恢复负荷供电等约束条件下,将供电网络的故障恢复看作是一个多目标、非线性优化问题。给出了节点电压约束的供电恢复模型,采用负载支路相关矩阵法对容量约束进行检验,减小了分析、计算难度。对负载进行0、1、2编码,每一位编码对应一个负载,有效地缩短了编码长度。最后应用克隆算法得出了优化的故障恢复策略,选择亲和力高的抗体并进行克隆。仿真结果表明,该算法比简单遗传算法、启发式遗传算法以及混沌遗传算法等其他故障恢复优化算法具有更快的收敛速度,更高的获得最优解的概率,能够有效提高故障恢复的速度和准确性。

To resolve service restoration of shipboard electrical power system, it is regarded as a multiobject nonlinear optimization problem after considering constrained conditions such as topological structure of ringy power supply network of multi-power station, capacity limitaiton of generator, load priority and maximum service restoration. In this paper, the service restoration model is presented under the restriction by node voltage, load branch correlative matrix method is applied to verify capacity limitaiton that can decrease analysis and computation complex. All loads are coded as 0,1 and 2, one bit corresponds to one load so that coding length is shortened. Clonal algorithm is adopted to educe optimized service restoration strategy, through selecting and clone antibody with high affinity. Simulation results indicate that service restoration method based on clonal algorithm has faster convergencing rate and higher probability of optimal solution compard with that of simple genetic algorithm, heuristic genetic algorithm and chaotic genetic algorithm.