State Estimation in Power Systems: Detecting Bad Data through the Sparse Inverse Matrix Method

1978 ◽  
Vol PAS-97 (3) ◽  
pp. 678-682 ◽  
Author(s):  
F. Broussolle
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Matrix Method ◽  
Inverse Matrix ◽  
Bad Data

scholarly journals Methodology for Implementing the State Estimation in Renewable Energy Management Systems

Energies ◽  
2021 ◽  
Vol 14 (8) ◽  
pp. 2301
Author(s):  
Yun-Sung Cho ◽  
Yun-Hyuk Choi
Keyword(s):  
Renewable Energy ◽  
Power Systems ◽  
State Estimation ◽  
Measurement Errors ◽  
Large Scale ◽  
Test System ◽  
The State ◽  
Inner Function ◽  
Outer Function ◽  
Bad Data

This paper describes a methodology for implementing the state estimation and enhancing the accuracy in large-scale power systems that partially depend on variable renewable energy resources. To determine the actual states of electricity grids, including those of wind and solar power systems, the proposed state estimation method adopts a fast-decoupled weighted least square approach based on the architecture of application common database. Renewable energy modeling is considered on the basis of the point of data acquisition, the type of renewable energy, and the voltage level of the bus-connected renewable energy. Moreover, the proposed algorithm performs accurate bad data processing using inner and outer functions. The inner function is applied to the largest normalized residue method to process the bad data detection, identification and adjustment. While the outer function is analyzed whether the identified bad measurements exceed the condition of Kirchhoff’s current law. In addition, to decrease the topology and measurement errors associated with transformers, a connectivity model is proposed for transformers that use switching devices, and a transformer error processing technique is proposed using a simple heuristic method. To verify the performance of the proposed methodology, we performed comprehensive tests based on a modified IEEE 18-bus test system and a large-scale power system that utilizes renewable energy.

Dynamic state estimation including bad data suppression for electric power systems

1979 ◽  
Vol 99 (4) ◽  
pp. 33-44 ◽  
Author(s):  
Ken-Ichi Nishiya ◽  
Hiroshi Takagi ◽  
Jun Hasegawa ◽  
Toichiro Koike
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Electric Power ◽  
Electric Power Systems ◽  
Dynamic State ◽  
Dynamic State Estimation ◽  
Bad Data

Observability analysis and bad data processing for state estimation using Hachtel's augmented matrix method

1988 ◽  
Vol 3 (2) ◽  
pp. 604-611 ◽  
Author(s):  
F.F. Wu ◽  
W.-H.E. Liu ◽  
L. Holten ◽  
L. Gjelsvik ◽  
S. Aam
Keyword(s):  
Data Processing ◽  
State Estimation ◽  
Matrix Method ◽  
Observability Analysis ◽  
Bad Data
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