IEEE Transactions on Instrumentation and Measurement · 2017 · 40 citations · 13 references
EngineeringElectrical EngineeringCircuit TheoryInstrumentationMethod ValidationElectrical MeasurementElectrical MetrologyParameter EstimationPower QualityState EstimationTransmission LinesFault LocationImpedance MeasurementImpedance MetrologyImpedance ModelingImpedance ParametersSystematic ErrorsTransmission Line AnalysisTransmission Line Modeling
Transmission line impedance parameter estimation is essential for modeling and monitoring electricity networks, influencing state estimation, fault location, and dynamic thermal line rating, yet existing methods often ignore systematic errors from instrumentation that degrade accuracy. This paper proposes a novel method that estimates correction factors for systematic instrumentation errors to improve impedance parameter accuracy. The method is evaluated against an existing approach using laboratory measurements in a case study.
Transmission line impedance parameter estimation forms an essential part in modeling and monitoring of electricity networks. The accuracy of the estimated parameters has a direct impact on various functions of network operation, such as state estimation, fault location, and dynamic thermal line rating. Impedance parameters can be estimated from voltage and current measurements taken at the ends of the transmission line. Previous research has produced a range of methods with the purpose of maximizing the accuracy of the estimated values. However, the input measurements from the line ends can contain systematic errors that are introduced by the instrumentation channel and significantly reduce impedance parameter accuracy, which is not taken into account by most of the existing methods. In this paper, a novel method is presented that estimates correction factors for the systematic errors and, thus, increases the accuracy of impedance parameter values. The performance of the new method is compared with an existing one in a case study on laboratory measurements.
13
Power system parameter estimation: a survey
P. Zarco · IEEE Transactions on Power Systems · 2000 · 216 citations · Full text
Engineering, Electrical Engineering, Systems Engineering +13