含阀点效应最优潮流问题的改进原始蚁群算法解  

Improved Primitive Ant Colony Algorithm for Optimal Power Flow Problem with Valve-point Effect

作　　者：罗中良[1] 李先祥[1] 方清城[1] 

机构地区：[1]佛山科学技术学院电气工程及自动化系,广东佛山528000

出　　处：《中山大学学报（自然科学版）》2006年第6期31-34,共4页Acta Scientiarum Naturalium Universitatis Sunyatseni

基　　金：广东省自然科学基金资助项目(020118)

摘　　要：基于原始蚁群的猎食行为提出一种新型的算法,称为改进原始蚁群算法,用于求解最优潮流问题。新算法只考虑离散变量,以降低计算时间,同时使用序列二次规划法求解连续变量。通过运用曲线分段的方法,使改进算法能处理含大量约束条件的各种目标函数并有效地搜索全局最优解。通过IEEE-30节点系统的仿真计算验证了该算法的有效性。An innovative Improved Primitive Ant Colony Algorithm （IPACA） based on primitive ants foraging behaviors is developed to solve the optimal power flow （OPF） problems with valve-point effect. IPACA only models the discrete control variables to reduce the calculation time, and use Sequential Quadratic Programming （SQp） to solves the state variables and the continuous control variables. A number of functional operating constraints are included as penalties in the objective cost function. With the idea of segmented curves, this new algorithm can easily handle various cost functions and efficiently search for the global minimum. Numerical simulations on IEEE -30 buses have shown that the proposed method is efficient in solving OPF.

关 键 词：最优潮流 改进式原始蚁群算法 序列二次规划法 曲线分段 

分 类 号：TM744[电气工程—电力系统及自动化]