Open AccessResearch onWeighted Least Square and Linear State Estimation Methods under Ill Condition of Power System
Author(s) -
M.S.N.G. Sarada Devi,
Thippiripati Vinay Kumar,
Dr.G. Yesuratnam
Publication year - 2019
Publication title -
international journal of engineering and advanced technology
Language(s) - English
Resource type - Journals
ISSN - 2249-8958
DOI - 10.35940/ijeat.b5143.129219
Subject(s) - jacobian matrix and determinant , electric power system , control theory (sociology) , matlab , state (computer science) , voltage , state vector , convergence (economics) , power (physics) , square (algebra) , mathematics , linear system , computer science , engineering , algorithm , mathematical analysis , electrical engineering , physics , classical mechanics , geometry , control (management) , quantum mechanics , artificial intelligence , economic growth , economics , operating system
A Jacobian matrix is said to be ill-conditioned if it is very sensitive to small changes. In this paper, the performance of Weighted Least Square (WLS) and Linear State Estimation (LSE) methods under stressed condition and ill condition of power system are compared. In weighted least square method, real/ reactive power injections/flows with very few bus voltage magnitudes are used to obtain the state vector (bus voltages) for given network model. This method inclined to convergence errors when the system is in stressed state or ill condition state. In Linear State Estimation method, bus voltage and current measurements are used to obtain the state vector. Because of its linear nature, LSE method is suitable under stressed condition/ ill condition of power systems. IEEE 14 bus, 13 bus ill conditioned system and EHV 24 bus systems are used in matlab environment to examine the proposed (LSE) method and simulation results are summarized.