摘要
基于过滤集合的内点算法是在传统原对偶内点法的基础上引入了可更新的过滤集合。由于采用过滤集合代替了传统的罚函数方法,该算法可以有效避免惩罚系数对算法收敛性和收敛速度的影响。同时过滤集合在迭代过程中会不断地更新,以确保在下一次迭代时新的运行点不会返回到上次迭代点的邻域内,从而解决了在迭代过程中发生振荡而导致算法难以收敛的问题。应用该方法求解电力系统无功优化问题时能有效处理目标函数中的大量不等式约束。对IEEE30、57、118标准算例的分析和试算表明,所提算法具有很好的收敛性,运算速度快。
The interior-point filter algorithm （IPFA） is based on a primal-dual interior-point algorithm with a filter set which can be updated after every iteration. The filter replaces the use of merit functions, which can avoid the influence of penalty parameters on the convergence of algorithm and convergence speed in merit functions. And the filter set will update continuously after every iteration, ensuring that the iterates cannot return to the neighborhood of the previous iterate. Over all, these procedures ensure that the algorithm cannot cycle between two points that alternatively decrease the constraint violation and the barrier objective function. Using IPFA for power system reactive optimization a large number of inequality constraints in the objective function can be effectively dealt with. The simulation results from tEEE 30-bus system, IEEE 57-bus system and IEEE 118-bus system show that the proposed algorithm possesses good robustness and fast convergence.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2011年第18期14-19,37,共7页
Power System Protection and Control
关键词
电力系统
无功优化
原-对偶内点法
过滤集合
不等式约束
power system
reactive power optimization
primal-dual interior-point algorithm
filter set
inequality constraint
