This paper proposes tabu search based static state estimation for DistFlow in radial distribution systems. DistFlow is more efficient than the conventional power flow calculation methods for distribution systems. It has a feature that state variables at the substation successively determine the rest of state variables. Recently, the automation for distribution systems has been popular to smooth more reliable distribution power system operation and planning. As a result, state estimation is required to compute reliable data. This paper develops the DistFlow-based static state estimation technique with tabu search. In this paper, the state estimation may be formulated as a minimization problem that determines state variables at the source node. As one of meta-heuristics, tabu search is applied to the problem so that an approximate solution near a globally optimal solution is obtained as an estimate with high accuracy. The proposed method is tested a 69-node system.
|Number of pages||7|
|Publication status||Published - 1 Dec 1999|
|Event||Proceedings of the 1999 Artificial Neural Networks in Engineering Conference (ANNIE '99) - St. Louis, MO, USA|
Duration: 7 Nov 1999 → 10 Nov 1999
|Conference||Proceedings of the 1999 Artificial Neural Networks in Engineering Conference (ANNIE '99)|
|City||St. Louis, MO, USA|
|Period||7/11/99 → 10/11/99|