Sustainable Method Using Filtering Techniques for a Fermentation Process State Estimation

On Line Electric Power Systems State Estimation Using Kalman Filtering (RESEARCH NOTE)

In this paper principles of extended Kalman filtering theory is developed and applied to simulated on-line electric power systems state estimation in order to trace the operating condition changes through the redundant and noisy measurements. Test results on IEEE 14 - bus test system are included. Three case systems are tried; through the comparing of their results, it is concluded that the pro...

Robust state estimation in power systems using pre-filtering measurement data

State estimation is the foundation of any control and decision making in power networks. The first requirement for a secure network is a precise and safe state estimator in order to make decisions based on accurate knowledge of the network status. This paper introduces a new estimator which is able to detect bad data with few calculations without need for repetitions and estimation residual cal...

An Advanced State Estimation Method Using Virtual Meters

-  Power system state estimation is a central component in energy management systems of power system. The goal of state estimation is to determine the system status and power flow of transmission lines. This paper presents an advanced state estimation algorithm based on weighted least square (WLS) criteria by introducing virtual meters. For each bus of network, except slack bus, a virtual meter...

Filtering and State Estimation

Box particle filtering for nonlinear state estimation using interval analysis

In recent years particle …lters have been applied to a variety of state estimation problems. A particle …lter is a sequential Monte Carlo Bayesian estimator of the posterior density of the state using weighted particles. The e¢ ciency and accuracy of the …lter depend mostly on the number of particles used in the estimation and on the propagation function used to re-allocate weights to these par...