摘要
针对遗传算法求解到一定范围容易产生大量冗余迭代、求解精度低,蚁群算法初期信息素匮乏、求解速度慢的缺陷,在电网规划算法中,将遗传算法与蚁群算法融合,在网架规划初期采用遗传算法求解出最优解,通过最优解生成蚁群算法的初期信息素,确定吸引强度的初始值,建立强度更新的模型,从而得到满足电网规划的最优方案。最后通过18节点的算例证明,融合算法在收敛性与寻优性上均得到提高。
Aimed at the problems of low solution precision by genetic algorithm and slow resolving speed by ant algorithm,the paper presented a hybrid algorithm based on genetic algorithm and ant algorithm.The optimal solution prepared by genetic algorithm formed initial pheromone of ant algorithm at first step of power network planning,and than the initial value of attraction intensity was confirmed,the model of intensity updating was set up,the optimal scheme was assured.At last,the hybrid algorithm was applied to 18-node example.The results showed that compared with genetic algorithm and ant algorithm,the hybrid algorithm had better quality in convergence and searching ability.
出处
《电力需求侧管理》
2011年第2期12-15,共4页
Power Demand Side Management
关键词
遗传算法
蚁群算法
融合算法
电网规划
genetic algorithm
ant algorithm
hybrid algorithm
power network planning
