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**Harvard**

Hagmar, H. (2016) *Accuracy Evaluation of Power System State Estimation - An evaluative study of the accuracy of state estimation with application to parameter estimation*. Göteborg : Chalmers University of Technology

** BibTeX **

@mastersthesis{

Hagmar2016,

author={Hagmar, Hannes},

title={Accuracy Evaluation of Power System State Estimation - An evaluative study of the accuracy of state estimation with application to parameter estimation},

abstract={The following report examines the impact that parameter and model errors have on the result of the power system state estimation. Furthermore, the feasibility of increasing the accuracy of the state estimation is examined by introducing parameter estimation within the ordinary estimation model.
Model errors due to unbalanced grid conditions are found to have a large impact on the phase values, but an almost negligible impact on the averaged values that are commonly used as input to the state estimation model. Parameter errors affect the accuracy of the state estimation in various extents, and errors in the line susceptance are found to generally cause the largest errors. The level of measurement redundancy is significant to the result, and reduced measurement redundancy will in general increase the estimation errors due to parameter errors. Furthermore, undesirable combinations of parameter errors within a larger network are also found to increase the estimation errors significantly. In order to estimate the magnitude of estimation errors caused by parameter errors, each grid configuration and power flow state would have to be examined individually.
Parameter estimation was found to be highly accurate in estimating the line susceptance for most levels of reasonable measurement errors. However, the line conductance and shunt susceptance were found to be significantly harder to estimate and even small measurement errors resulted in poor estimations. Using parameter estimation for the line susceptance under conditions of relatively low levels of measurement errors was found to significantly decrease the errors in the state estimation. Finally, an alternative method of estimating the line conductance was examined. This estimation was found to be more resilient to errors in the voltage measurement, but was still sensitive to errors in the power flow measurement devices.},

publisher={Institutionen för energi och miljö, Elteknik, Chalmers tekniska högskola},

place={Göteborg},

year={2016},

keywords={State estimation, parameter estimation, sensitivity analysis, parameter errors, model errors, SP, Svenska kraftnät, accuracy evaluation, state estimation accuracy enhancement},

note={70},

}

** RefWorks **

RT Generic

SR Electronic

ID 241106

A1 Hagmar, Hannes

T1 Accuracy Evaluation of Power System State Estimation - An evaluative study of the accuracy of state estimation with application to parameter estimation

YR 2016

AB The following report examines the impact that parameter and model errors have on the result of the power system state estimation. Furthermore, the feasibility of increasing the accuracy of the state estimation is examined by introducing parameter estimation within the ordinary estimation model.
Model errors due to unbalanced grid conditions are found to have a large impact on the phase values, but an almost negligible impact on the averaged values that are commonly used as input to the state estimation model. Parameter errors affect the accuracy of the state estimation in various extents, and errors in the line susceptance are found to generally cause the largest errors. The level of measurement redundancy is significant to the result, and reduced measurement redundancy will in general increase the estimation errors due to parameter errors. Furthermore, undesirable combinations of parameter errors within a larger network are also found to increase the estimation errors significantly. In order to estimate the magnitude of estimation errors caused by parameter errors, each grid configuration and power flow state would have to be examined individually.
Parameter estimation was found to be highly accurate in estimating the line susceptance for most levels of reasonable measurement errors. However, the line conductance and shunt susceptance were found to be significantly harder to estimate and even small measurement errors resulted in poor estimations. Using parameter estimation for the line susceptance under conditions of relatively low levels of measurement errors was found to significantly decrease the errors in the state estimation. Finally, an alternative method of estimating the line conductance was examined. This estimation was found to be more resilient to errors in the voltage measurement, but was still sensitive to errors in the power flow measurement devices.

PB Institutionen för energi och miljö, Elteknik, Chalmers tekniska högskola,

LA eng

LK http://publications.lib.chalmers.se/records/fulltext/241106/241106.pdf

OL 30