Identification and updating of minimally dependent sets of measurements in state estimation
Authors:
- G.N. KorresGKG.N. Korres
- G.C. ContaxisGCG.C. Contaxis
- 1 January 1991
- journal article
- Published by Institute of Electrical and Electronics Engineers (IEEE) in IEEE Transactions on Power Systems
- Vol. 6 (3) , 999-1005
Abstract
In this paper a new algorithm for the identification and updating of minimally dependent sets of measurements is presented. The technique implemented in the algorithm is a mixed numerical-symbolic method based on a reduced model and graph theory. As a byproduct of the algorithm, critical measurements and error residual spread areas are provided. Emphasis is placed in the updating of the above quantities when one or more measurements are eliminated from the measurement set. Computational aspects of the proposed algorithm are discussed and results from an illustrative example and test cases are reportedKeywords
This publication has 7 references indexed in Scilit:
- A reduced model for bad data processing in state estimationIEEE Transactions on Power Systems, 1991
- Qualitative methods to solve qualitative problems in power system state estimationIEEE Transactions on Power Systems, 1990
- A reduced model for power system observability: analysis and restorationIEEE Transactions on Power Systems, 1988
- Bad Data Groups in Power System State EstimationIEEE Transactions on Power Systems, 1986
- Hypothesis Testing Identification: A New Method For Bad Data Analysis In Power System State EstimationIEEE Transactions on Power Apparatus and Systems, 1984
- Power System State Estimation with Measurement Deficiency: an Observability/Measurement Placement AlgorithmIEEE Transactions on Power Apparatus and Systems, 1983
- State Estimation in Power Systems: Detecting Bad Data through the Sparse Inverse Matrix MethodIEEE Transactions on Power Apparatus and Systems, 1978