Título
Uncertainty Distribution Assessment of Jiles-Atherton Parameter Estimation for Inrush Current StudiesGrupo de investigación
Accionamientos aplicados a la tracción y a la generación de energía eléctricaSistemas electrónicos de potencia aplicados al control de la energía eléctrica
Otras instituciones
IkerbasqueVersión
Postprint
Derechos
© 2024 IEEEAcceso
Acceso abiertoVersión del editor
https://doi.org/10.1109/TPWRD.2024.3398790Publicado en
IEEE Transactions on Power Delivery Editor
IEEEPalabras clave
inrush current
Transformers
Jiles-Atherton model
metaheuristic-based search ... [+]
Transformers
Jiles-Atherton model
metaheuristic-based search ... [+]
inrush current
Transformers
Jiles-Atherton model
metaheuristic-based search
Probability density function
uncertainty
ODS 9 Industria, innovación e infraestructura [-]
Transformers
Jiles-Atherton model
metaheuristic-based search
Probability density function
uncertainty
ODS 9 Industria, innovación e infraestructura [-]
Resumen
Transformers are one of the key assets in AC distribution grids and renewable power integration. During transformer energization inrush currents appear, which lead to transformer degradation and can c ... [+]
Transformers are one of the key assets in AC distribution grids and renewable power integration. During transformer energization inrush currents appear, which lead to transformer degradation and can cause grid instability events. These inrush currents are a consequence of the transformer's magnetic core saturation during its connection to the grid. Transformer cores are normally modelled by the Jiles-Atherton (JA) model which contains five parameters. These parameters can be estimated by metaheuristic-based search algorithms. The parameter initialization of these algorithms plays an important role in the algorithm convergence. The most popular strategy used for JA parameter initialization is a random uniform distribution. However, techniques such as parameter initialization by Probability Density Functions (PDFs) have shown to improve accuracy over random methods. In this context, this research work presents a framework to assess the impact of different parameter initialization strategies on the performance of the JA parameter estimation for inrush current studies. Depending on available data and expert knowledge, uncertainty levels are modelled with different PDFs. Moreover, three different metaheuristic-search algorithms are employed on two different core materials and their accuracy and computational time are compared. Results show an improvement in the accuracy and computational time of the metaheuristic-based algorithms when PDF parameter initialization is used. [-]
Financiador
Gobierno de EspañaPrograma
Convocatoria 2021. Programa Estatal para Impulsar la Investigación Científico-Técnica y su Transferencia, del Plan Estatal de Investigación Científica, Técnica y de Innovación 2021-2023Número
CPP2021-008580URI de la ayuda
Sin informaciónProyecto
Modelización y Diagnóstico de Transformadores (MODITRANS)Colecciones
- Artículos - Ingeniería [639]