Static State Estimation in Electric Power Systems
GPTKB entity
Statements (42)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
scientific theory
|
| gptkbp:application |
energy management systems
power system control power system operation power system planning |
| gptkbp:appliesTo |
electric power systems
|
| gptkbp:citation |
gptkb:A._Monticelli,_State_Estimation_in_Electric_Power_Systems:_A_Generalized_Approach
A. Abur and A. G. Expósito, Power System State Estimation: Theory and Implementation |
| gptkbp:class |
gptkb:Weighted_Least_Squares_Estimation
|
| gptkbp:developedBy |
1970s
|
| gptkbp:enables |
anomaly detection
real-time monitoring bad data detection network security analysis |
| gptkbp:field |
Electrical Engineering
|
| gptkbp:form |
nonlinear equations
linearized models |
| https://www.w3.org/2000/01/rdf-schema#label |
Static State Estimation in Electric Power Systems
|
| gptkbp:improves |
system security
system reliability system efficiency |
| gptkbp:input |
bus voltage angles
bus voltage magnitudes power flows power injections |
| gptkbp:keyChallenge |
incomplete data
measurement errors network observability |
| gptkbp:output |
estimated system state
|
| gptkbp:purpose |
determine the most probable state of a power system
|
| gptkbp:relatedTo |
gptkb:Dynamic_State_Estimation
gptkb:Phasor_Measurement_Units_(PMU) gptkb:Supervisory_Control_and_Data_Acquisition_(SCADA) |
| gptkbp:supportsAlgorithm |
gptkb:Newton-Raphson_method
gptkb:Gauss-Newton_method Kalman filter (for dynamic extension) Least Absolute Value estimation |
| gptkbp:uses |
mathematical models
optimization techniques measurement data |
| gptkbp:bfsParent |
gptkb:Charles_H._Schweppe
|
| gptkbp:bfsLayer |
6
|