Fast Power System State Estimation Based on Weighted Least Squares Algorithm with Constant Matrices

2018 ◽  
Author(s):  
Meriem Majdoub ◽  
Jamal Boukherouaa ◽  
Bouchra Cheddadi ◽  
Abdelaziz Belfqih ◽  
Omar Sabri ◽  
...  
Keyword(s):  
Power System ◽  
Least Squares ◽  
State Estimation ◽  
Weighted Least Squares ◽  
System State ◽  
Power System State Estimation ◽  
Fast Power ◽  
Least Squares Algorithm

Regularized Least Squares Power System State Estimation

2012 ◽  
Vol 27 (1) ◽  
pp. 290-297 ◽  
Author(s):  
Madson C. de Almeida ◽  
Ariovaldo V. Garcia ◽  
Eduardo N. Asada
Keyword(s):  
Power System ◽  
Least Squares ◽  
State Estimation ◽  
System State ◽  
Regularized Least Squares ◽  
Power System State Estimation

scholarly journals Full versus decoupled constant matrices to speed up power system state estimation

2020 ◽  
Vol 11 (3) ◽  
pp. 1287
Author(s):  
Meriem Majdoub ◽  
Bouchra Cheddadi ◽  
Omar Sabri ◽  
Abdelaziz Belfqih ◽  
Jamal Boukherouaa
Keyword(s):  
Power System ◽  
State Estimation ◽  
Distribution Systems ◽  
Weighted Least Squares ◽  
Computation Time ◽  
System State ◽  
Transmission Systems ◽  
Power System State Estimation ◽  
Slowing Down ◽  
Speed Up

This paper presents a performance evaluation of two solutions to reduce computational burden of the traditional Weighted Least Squares Algorithm for power system state estimation: Simplified methods SWLS1 / SWLS2 based on full constant matrices and Fast decoupled FDWLS based on decoupled constant matrices. First, the algorithms were tested on IEEE 14 and 118 bus transmission systems. Second, the solutions were tested on a rural distribution feeder to evaluate the response of the algorithms to high R/X ratio. Results show that for transmission systems, FDWLS is the fastest method but more sensitive to erroneous measurements. Simplifications considered in FDWLS, are not valid in distribution systems with high R/X ratio this results in slowing down the algorithm convergence speed considerably compared to SWLS2 which performs well. SWLS2 algorithm presents a promising solution to reduce computation time for application in future smart grid.

POWER SYSTEM STATE ESTIMATION USING A ROBUST ESTIMATOR

2019 ◽  
Vol XVI (4) ◽  
pp. 53-65
Author(s):  
Zahid Khan ◽  
Katrina Lane Krebs ◽  
Sarfaraz Ahmad ◽  
Misbah Munawar
Keyword(s):  
Power Systems ◽  
State Estimation ◽  
Loss Function ◽  
Weighted Least Squares ◽  
Primary Data ◽  
Robust Estimator ◽  
System State ◽  
State Estimator ◽  
Suggested Approach ◽  
Power System State Estimation

State estimation (SE) is a primary data processing algorithm which is utilised by the control centres of advanced power systems. The most generally utilised state estimator is based on the weighted least squares (WLS) approach which is ineffective in addressing gross errors of input data of state estimator. This paper presents an innovative robust estimator for SE environments to overcome the non-robustness of the WLS estimator. The suggested approach not only includes the similar functioning of the customary loss function of WLS but also reflects loss function built on the modified WLS (MWLS) estimator. The performance of the proposed estimator was assessed based on its ability to decrease the impacts of gross errors on the estimation results. The properties of the suggested state estimator were investigated and robustness of the estimator was studied considering the influence function. The effectiveness of the proposed estimator was demonstrated with the help of examples which also indicated non-robustness of MWLS estimator in SE algorithm.

MODEL‐BASED ANOMALY DETECTION FOR POWER SYSTEM STATE ESTIMATION

2020 ◽  
pp. 99-121
Author(s):  
Aditya Ashok ◽  
Manimaran Govindarasu ◽  
Venkataramana Ajjarapu
Keyword(s):  
Anomaly Detection ◽  
Power System ◽  
State Estimation ◽  
System State ◽  
Power System State Estimation ◽  
Model Based
Sign in / Sign up

Export Citation Format

Share Document