摘要
加权最小二乘法是状态估计的常用方法,但在实际应用中经常会遇到算法发散的问题。为了解决这个问题,提出将改进的粒子群进化算法应用到状态估计当中,使加权最小二乘法的收敛性得到了很好的改善。结合IEEE5节点系统,给出了粒子群进化状态估计计算的三点注意事项。经试验得出,对量测点数为16的系统而言,计算时间在50s左右,量测点数为30的系统的计算时间在3min左右,量测点数为80的系统,其计算时间在15min左右。这种算法可以应用在离线状态估计上。
The least robustness square method is a common method in power system state estimation, but we find that it is difficult to solve the problem of divergence in practical applications. To solve this problem, an improved particle swarm optimization algorithm is applied to state estimation and it can help with the improving of convergence of least robustness square method. Combined with IEEE 5 bus system, three notes are provided in particle swarm optimization algorithm state estimation. The experiment proves that the calculation time is about fifty seconds for sixteen points system and the calculation time is about three minutes for thirteen points system and fifteen minutes for eighty points system. This method can be applied to out-line state estimation.
出处
《电力系统保护与控制》
EI
CSCD
北大核心
2010年第22期86-89,95,共5页
Power System Protection and Control
基金
黑龙江省普通高校骨干教师创新能力资助计划(1152G003)
关键词
粒子群进化算法
电力系统
状态估计
加权最小二乘法
收敛
particle swarm optimization algorithm
power system
state estimation
least robustness square method
convergence
