This paper presents a new method for QP-based power system state estimation using an artificial neural network. QP-based state estimation makes use of the fact that the observation equation is expressed as a set of exact quadratic equations in rectangular coordinate. The problem formulation is transformed into evaluating equilibriums of the differential equations with an artificial neural network that is based on the Lagrange function. Thus, the obtained solution is optimal in a sense of the Kuhn-Tucker conditions.
|Number of pages||4|
|Journal||Proceedings - IEEE International Symposium on Circuits and Systems|
|Publication status||Published - 1 Jan 1996|
|Event||Proceedings of the 1996 IEEE International Symposium on Circuits and Systems, ISCAS. Part 1 (of 4) - Atlanta, GA, USA|
Duration: 12 May 1996 → 15 May 1996