基于飞蛾扑火优化算法的电力系统最优潮流计算  

Optimal Power Flow Calculation With Moth-Flame Optimization Algorithm

作　　者：王子琪 陈金富[1] 张国芳[2] 杨琪[2] 代宇涵 

机构地区：[1]强电磁工程与新技术国家重点实验室(华中科技大学电气与电子工程学院),湖北省武汉市430074 [2]国网四川省电力公司,四川省成都市610041 [3]国网四川省电力公司电力科学研究院,四川省成都市610072

出　　处：《电网技术》2017年第11期3641-3647,共7页Power System Technology

摘　　要：飞蛾扑火优化(moth-flame optimization,MFO)算法作为一种最新提出的启发式智能优化算法,具有优良的搜索性能和鲁棒性,可用于求解复杂实际工程问题。针对电力系统最优潮流问题,提出采用MFO算法的最优化求解方案。该方案采用发电成本以及发电成本结合有功网损、节点电压偏移的加权和作为优化问题的目标函数,考虑电力系统潮流计算中复杂的约束限制,并与现有的基于其他智能优化算法的最优潮流计算结果展开对比与分析。IEEE 30节点系统仿真算例结果表明,采用MFO算法求解最优潮流问题具有收敛速度更快、搜索精度更高、鲁棒性强等优点。Moth-flame optimization（MFO） algorithm can be used to solve practical complex engineering problems as a novel nature-inspired intelligence optimization algorithm with excellent searching and robustness performance.To solve optimal power flow problem in power system,this paper proposes an MFO-based optimal solution scheme.In the scheme,generation cost and its weighted sum with active power loss or node voltage deviation are taken as objective functions of the optimization problem,respectively.Complex constraints in optimal power flow are taken into account.Optimization results of the proposed MFO algorithm are compared with those of other intelligence algorithms.Simulation results of IEEE 30-bus test system indicate that MFO algorithm has advantages of more efficient convergence speed,higher search accuracy and stronger robustness in solving optimal power flow problem.

关 键 词：最优潮流计算 飞蛾扑火优化算法 智能优化算法 算法性能评估 

分 类 号：TM721[电气工程—电力系统及自动化]