Flow field estimation analysis based on the Kalman filter FEM for selection of tidal stream power generator locations

Abstract

In this paper, we present a shallow water flow field estimation analysis, based on the Kalman filter FEM, for locating the optimal positions for tidal stream power generation systems. In our flow field analysis, we adopt the shallow water equation as the governing equation. The Galerkin and the selective lumping methods are employed as discretization techniques in space and time, respectively. The Kalman filter theory is applied to estimate the flow field. As a numerical example, we cany out a flow estimation analysis for Tokyo Bay. The high estimation accuracy of the flow field estimation based on the Kalman filter FEM is confirmed by comparison with conventional FEM. The electric power generation potential is also computed using the estimated flow field.