会议专题

Modeling of Electric Power Transformer Using Complex-Valued Neural Networks

Accurate simulation of a power grid requires use of detailed power equipment models in order to reflect maximum of complex dynamics occurs in the grid.Conventional approaches are not always sufficient to fulfill necessity of meticulous description of processes in power devices.Existence of physical difference even between devices of exactly the same type pulls the accuracy of the whole grid simulation using one model for each type of equipment down.A completely new approach of power equipment modeling - modeling based on Complex-Valued Neural Networks (CVNN) -gives an opportunity to build a high-quality models which are able to track dynamics of grid devices.The nature of the approach makes it relatively easy to build models of all electric network devices even individually taking into account the uniqueness of each one.Power transformer, being quite common and, generally, complicated nonlinear element of power grid, has been chosen for demonstration of CVNN method.Results obtained from this work show that application of CVNN in power engineering modeling appears as quite promising method.

complex-vaued neural network CVNN transformer modeling power equipment modeling

Yury S. Chistyakov Elena V. Kholodova Alexey S. Minin Hans-Georg Zimmermann Alois Knoll

Corporate Technology Department,Siemens LLC,Volynskiy lane 3,191186,St.Petersburg,Russia Corporate Technology Department,Siemens LLC,Letnikovskaya str.10/11,115114,Moscow,Russia Corporate Technology Department,Siemens LLC,Volynskiy lane 3,191186,St.Petersburg,also with the Dept Corporate Technology Department,Siemens AG,D-81730 Muenchen,Mch-P,R.53.220 Technical University of Munich.BoltzmannstraBe 3,85748 Garching bei Munchen,Germany

国际会议

2011 IEEE International Conference on Smart Grid and Clean Energy Technologies(2011 IEEE智能电网与清洁能源技术国际会议 ICSGCE2011)

成都

英文

387-391

2011-09-27(万方平台首次上网日期,不代表论文的发表时间)