scholarly journals A Synchrophasor Assisted Hybrid State Estimator

2016 ◽  
Vol 67 (2) ◽  
pp. 103-110
Author(s):  
Vedran Kirincic ◽  
Srdjan Skok ◽  
Dubravko Frankovic
Keyword(s):  
Measurement Errors ◽  
Recursive Algorithm ◽  
State Estimator ◽  
Final State ◽  
Hybrid State ◽  
State Estimators ◽  
System Part ◽  
Measurement Units ◽  
Improved Accuracy ◽  
The Given

Abstract The paper presents a Synchrophasor Assisted Hybrid State Estimator that utilizes the conventional SCADA measurements and the synchrophasors obtained from Phasor Measurement Units (PMUs). To take advantage of the high sampling frequency of the multiple sets of synchrophasors they are preprocessed in a recursive algorithm that provides the state estimate for the power system part observable by PMUs. The results are forwarded to an iterative procedure in which they are combined with SCADA measurements. The given solution was applied on the IEEE test systems with 14, 30 and 57 buses and its performance was compared with other state estimators. The filtering of measurement errors and convergence, while providing improved accuracy of the final state estimates of the developed methodology can be compared with other hybrid state estimators.

scholarly journals A Hybrid State Estimator using Current based Estimator and PMU Measurements

2017 ◽  
Vol 117 ◽  
pp. 1117-1124 ◽  
Author(s):  
S.P. Noopura ◽  
M.V. Jayan
Keyword(s):  
State Estimator ◽  
Hybrid State

Futuristic Prediction of Missing Value Imputation Methods Using Extended ANN

2022 ◽  
Vol 9 (3) ◽  
pp. 0-0
Keyword(s):  
Data Analysis ◽  
Missing Data ◽  
Measurement Errors ◽  
Missing Values ◽  
Missing Value ◽  
Hybrid Schemes ◽  
Imputation Methods ◽  
Research Fields ◽  
Data Missing ◽  
The Given

Missing data is universal complexity for most part of the research fields which introduces the part of uncertainty into data analysis. We can take place due to many types of motives such as samples mishandling, unable to collect an observation, measurement errors, aberrant value deleted, or merely be short of study. The nourishment area is not an exemption to the difficulty of data missing. Most frequently, this difficulty is determined by manipulative means or medians from the existing datasets which need improvements. The paper proposed hybrid schemes of MICE and ANN known as extended ANN to search and analyze the missing values and perform imputations in the given dataset. The proposed mechanism is efficiently able to analyze the blank entries and fill them with proper examining their neighboring records in order to improve the accuracy of the dataset. In order to validate the proposed scheme, the extended ANN is further compared against various recent algorithms or mechanisms to analyze the efficiency as well as the accuracy of the results.

A hybrid robust forecasting-aided state estimator considering bimodal Gaussian mixture measurement errors

2020 ◽  
Vol 120 ◽  
pp. 105962
Author(s):  
Zhaoyang Jin ◽  
Junbo Zhao ◽  
Saikat Chakrabarti ◽  
Lei Ding ◽  
Vladimir Terzija
Keyword(s):  
Measurement Errors ◽  
Gaussian Mixture ◽  
State Estimator
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