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SAIEE Africa Research Journal
On-line version ISSN 1991-1696
Print version ISSN 0038-2221
Abstract
RAHMAN, Ashfaqur and VENAYAGAMOORTHY, Ganesh Kumar. Convergence of the fast state estimation for power systems. SAIEE ARJ [online]. 2017, vol.108, n.3, pp.117-127. ISSN 1991-1696.
Power system state estimation is a fundamental computational process that requires both speed and reliability. To meet the needs, some variants of the constant Jacobian methods have been used in the industry over the last several decades. The variants work very well under normal operating conditions with nominal values of the states. However, the convergence of the methods are not analysed mathematically and it may contain pitfalls. In this study, the convergence of the constant Jacobian methods are analysed and it is shown that the methods fail under high variations of the states. To increase the reliability of the processes, a multi-Jacobian method is proposed. Through simulation, a special case is shown for IEEE 68, and IEEE 118-bus systems where the Jacobian calculated with the nominal value fails, and the proposed multi-Jacobian method succeeds.
Keywords : Convergence; dishonest Gauss Newton method; fast decoupled state estimator; parallel programming; weighted least squares estimator.