Blood, E.A.; B.H. Krogh and M.D. Ilic: Electric power system static state estimation through Kalman filtering and load forecasting, pp. 1-6. In: Proceedings of the Power and Energy Society General Meeting - Conversion and Delivery of Electrical Energy in the 21st Century, 20-24 July (2008). At: Pittsburgh, PA, USA. ISSN: 1932-5517. ISBN: 978-1-4244-1905-0. International Proceedings (refereed).
Static state estimation in electric power systems is normally accomplished without the use of time-history data or prediction. This paper presents preliminary work on the use of the discrete-time Kalman filter to incorporate time history and power demand prediction into state estimators. The problem of state estimation combined with the knowledge of the forecasted load is posed as a Kalman filtering problem using a novel discrete-time model. The model relates current and previous states using the electric power flow equations. An IEEE 14-bus test system example is used to illustrate the potential for enhanced performance of such Kalman filter-based state estimation