Dispersed Filters for Power System State Estimation

被引:0
作者
Kozierski, Piotr [1 ]
Lis, Marcin [1 ]
Owczarkowski, Adam [1 ]
Horla, Dariusz [1 ]
机构
[1] Poznan Univ Tech, Fac Elect Engn, Poznan, Poland
来源
2014 19TH INTERNATIONAL CONFERENCE ON METHODS AND MODELS IN AUTOMATION AND ROBOTICS (MMAR) | 2014年
关键词
dispersed filters; state estimation; particle filter; power system;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
The article proposes an approach to power system state estimation allowing the division of the network into smaller parts and performing calculations for each part at the same time. The latter can be implemented in parallel, but the main aim has been to propose a method for dispersed calculations, i.e. calculations that may be performed on computing units located at various points of the whole power system. In the paper, there are 3 algorithms for which dispersed versions have been proposed: Extended Kalman Filter, Particle Filter and Extended Kalman Particle Filter. As a result of the simulations, it has been verified that the Dispersed Particle Filter works better than simple Particle Filter. In two other cases, distributed algorithms work worse, but for the Extended Kalman Filter degradation in the estimation quality is not significant.
引用
收藏
页码:129 / 133
页数:5
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