What time-period aggregation method works best for power system operation models with renewablesand storage?
tipo de documento semantico ckh_publication
Ficheros
IIT-19-072A.pdf
Tamaño
334416
Formato
Adobe PDF
Url del contenido
https://repositorio.comillas.edu/rest/bitstreams/308569/retrieve
Fecha de publicación
09/09/2019
Fuente
Libro: 2nd International Conference on Smart Energy Systems and Technologies - SEST 2019, Página inicial: 1-6, Página final:
Estado
info:eu-repo/semantics/publishedVersion
Resumen
Idioma
es-ES
Idioma
en-GB
Resumen
In this paper we compare two cutting-edge timeperiod aggregation methodologies for power system models that consider both renewables and storage technologies: the chronological time-period clustering; and, the enhanced representative period approach. Such methodologies are used in order to reduce the computational burden of highly complex optimization models while not compromising the quality of the results. With this paper, we identify which method works best, and under which conditions, in order to reproduce the outcomes of the hourly benchmark model.
Uri identificador
http://hdl.handle.net/11531/40650
Editorial
Universidade do Porto; Instituto de Engenharia de Sistemas e Computadores, Tecnologia e Ciência (Oporto, Portugal)
Grupos de investigación y líneas temáticas
Instituto de Investigación Tecnológica (IIT)
Palabras clave
Tipo de archivo
application/pdf
Idioma
en-GB
Tipo de acceso
info:eu-repo/semantics/restrictedAccess
Fecha de modificacion
09/09/2022
Fecha de disponibilidad
11/09/2019
fecha de alta
11/09/2019