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提出了一种基于均匀设计的免疫克隆无功优化算法。该方法将初始种群均匀地分布在解空间中,使初始种群更多地表征解空间的信息,这样有利于在降低种群规模的同时保持种群多样性,有效提高算法的计算效率。提出了一种基于“距离”的疫苗接种策略,按照“距离”从大到小的原则确定接种位,有效地避免了“接种浪费”;引入克隆算法的高频变异操作,对每一代的最优个体进行邻域搜索,提高算法的局部搜索能力。对IEEE 30节点和IEEE 57节点系统进行仿真表明:该算法在种群规模较小的情况下依然具有计算效率高、收敛性好等优点,适合求解电力系统无功优化问题。
An immune clonal reactive power optimization algorithm based on uniform design is proposed. In this method, the initial population is uniformly distributed in the solution space so that the initial population can characterize the information of the solution space more. This helps to reduce the size of the population while maintaining the population diversity and effectively increasing the computational efficiency of the algorithm. A vaccination strategy based on “distance ” was proposed, and the inoculation position was determined according to the principle of “distance ” from big to small, effectively avoiding “waste of inoculation” , To search the best individual of each generation for neighborhood search and improve the local search ability of the algorithm. Simulation of IEEE 30-bus and IEEE 57-bus system shows that the proposed algorithm has the advantages of high computational efficiency and good convergence when the population size is small, and is suitable for solving the reactive power optimization problem in power system.