RT info:eu-repo/semantics/article
T1 Spectral kurtosis based methodology for the identification of stationary load signatures in electrical signals from a sustainable building
A1 Romero Ramirez, Luis Alejandro
A1 Elvira Ortiz, David Alejandro
A1 Romero Troncoso, René de Jesús
A1 Osornio Ríos, Roque A.
A1 Zorita Lamadrid, Ángel Luis
A1 González González, Sergio Lorenzo
A1 Moríñigo Sotelo, Daniel
K1 Signal processing - Digital techniques
K1 Tratamiento de señal - Técnicas numéricas
K1 Sustainable buildings
K1 Urbanismo - Aspecto del medio ambiente
K1 Renewable energy resources
K1 Energías renovables - Aspecto del medio ambiente
K1 Edificios sostenibles
K1 Arquitectura sostenible
K1 Total harmonic distortion
K1 Spectrum analysis - Statistical methods
K1 Análisis espectral - Métodos estadísticos
K1 Spectral kurtosis
K1 6201.03 Urbanismo
K1 3306 Ingeniería y Tecnología Eléctricas
K1 3308 Ingeniería y Tecnología del Medio Ambiente
AB The increasing use of nonlinear loads in the power grid introduces some unwanted effects, such as harmonic and interharmonic contamination. Since the existence of spectral contamination causes waveform distortion that may be harmful to the loads that are connected to the grid, it is important to identify the frequency components that are related to specific loads in order to determine how relevant their contribution is to the waveform distortion levels. Due to the diversity of frequency components that are merged in an electrical signal, it is a challenging task to discriminate the relevant frequencies from those that are not. Therefore, it is necessary to develop techniques that allow performing this selection in an efficient way. This paper proposes the use of spectral kurtosis for the identification of stationary frequency components in electrical signals along the day in a sustainable building. Then, the behavior of the identified frequencies is analyzed to determine which of the loads connected to the grid are introducing them. Experimentation is performed in a sustainable building where, besides the loads associated with the normal operation of the building, there are several power electronics equipment that is used for the electric generation process from renewable sources. Results prove that using the proposed methodology it is possible to detect the behavior of specific loads, such as office equipment and air conditioning.
PB MDPI
SN 1996-1073
YR 2022
FD 2022
LK https://uvadoc.uva.es/handle/10324/62467
UL https://uvadoc.uva.es/handle/10324/62467
LA eng
NO Energies, 2022, Vol. 15, Nº. 7, 2373
NO Producción Científica
DS UVaDOC
RD 14-oct-2024