Abstract
State estimators are vitally important in energy control centers. The measurements that come from control system are generally analysed by a state estimator. Since there can always be bad measurements in the system, estimated value and the true value of the state estimator can be far from each other. In this paper, by using an artificial neural network (ANN), a bad data detection, identification and then elimination preestimation filter is outlined.
Keywords
Estimator
Artificial neural network
Identification (biology)
State (computer science)
State estimator
Computer science
Estimation
Value (mathematics)
Artificial intelligence
Control (management)
Control theory (sociology)
Data mining
Machine learning
Statistics
Mathematics
Engineering
Algorithm
Subject Areas
Fault Detection and Control Systems
·Control and Systems Engineering ·Physical Sciences
Control Systems and Identification
·Control and Systems Engineering ·Physical Sciences
Target Tracking and Data Fusion in Sensor Networks
·Artificial Intelligence ·Physical Sciences
OpenAlex SDG Match
SDGs auto-classified by OpenAlex (score ≥ 0.4 shown).
Affordable and clean energy 90%
Loading…