@article { author = {Mahdavi Tabatabayee, N. and Kenarangui, R.}, title = {On Line Electric Power Systems State Estimation Using Kalman Filtering (RESEARCH NOTE)}, journal = {International Journal of Engineering}, volume = {8}, number = {4}, pages = {233-235}, year = {1995}, publisher = {Materials and Energy Research Center}, issn = {1025-2495}, eissn = {1735-9244}, doi = {}, abstract = {In this paper principles of extended Kalman filtering theory is developed and applied to simulated on-line electric power systems state estimation in order to trace the operating condition changes through the redundant and noisy measurements. Test results on IEEE 14 - bus test system are included. Three case systems are tried; through the comparing of their results, it is concluded that the proposed dynamic estimator have great advantage over the static state estimation in its accuracy and real time implementation.}, keywords = {state estimation,Kalman Filter,power systems}, url = {https://www.ije.ir/article_71137.html}, eprint = {https://www.ije.ir/article_71137_6647a39a135e64eb9ed29032fd1c28ec.pdf} }