A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation
Descripción del Articulo
The rapid growth of wind and solar generation has introduced significant variability and uncertainty into the operation of electric power systems (SEP), challenging traditional methods for sizing operating reserves. This article presents a dynamic probabilistic method based on the convolution of pro...
| Autor: | |
|---|---|
| Formato: | artículo |
| Fecha de Publicación: | 2025 |
| Institución: | Universidad de San Martín de Porres |
| Repositorio: | Revistas - Universidad de San Martín de Porres |
| Lenguaje: | español |
| OAI Identifier: | oai:revistas.usmp.edu.pe:article/3161 |
| Enlace del recurso: | https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161 |
| Nivel de acceso: | acceso abierto |
| Materia: | Wind and Solar Generation Dynamic Probabilistic Method Convolution Secondary Frequency Regulation Electric Power System Demand Generación Eólica y Solar Método Probabilístico Dinámico Convolución Regulación Secundaria de Frecuencia Sistema Eléctrico de Potencia Demanda |
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A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generationUn método probabilístico dinámico para determinarla reserva para regulación secundaria de frecuencia ensistemas eléctricos de potencia con alta integraciónde generación eólica y solarAracayo, JavierWind and Solar GenerationDynamic Probabilistic MethodConvolutionSecondary Frequency RegulationElectric Power SystemDemandGeneración Eólica y SolarMétodo Probabilístico DinámicoConvoluciónRegulación Secundaria de FrecuenciaSistema Eléctrico de PotenciaDemandaThe rapid growth of wind and solar generation has introduced significant variability and uncertainty into the operation of electric power systems (SEP), challenging traditional methods for sizing operating reserves. This article presents a dynamic probabilistic method based on the convolution of probability distribution functions, aimed at accurately estimating the reserve required for Secondary Frequency Regulation (RSF) in contexts with high penetration of intermittent renewable sources. The proposed approach employs historical time series data with halfhour resolution for electricity demand, wind generation, and solar generation, applying a discrete convolution technique to combine their respectiveprobability distributions. Unlike conventional methods, this methodology allows for differentiated reserve estimation according to the hour of the dayand the type of day (weekday or non-weekday), enhancing the precision and operational efficiency of the system. The validity of the method was assessed using data from the Peruvian power system, demonstrating its scalability and adaptability to other systems with increasing renewable energy participation.The results show significant improvements in the sizing and allocation of SFR, contributing to a more secure, efficient, and reliable operation of modernpower systems.El crecimiento acelerado de la generación eólica y solar ha introducido una considerable variabilidad e incertidumbre en la operación de los sistemas eléctricos de potencia (SEP), desafiando los métodos tradicionales de dimensionamiento de reservas operativas. Este artículo presenta un método probabilístico dinámico basado en la convolución de funciones de distribución de probabilidad, orientado a estimar con mayor precisión la reserva requerida para la Regulación Secundaria de Frecuencia (RSF) en contextoscon alta penetración de fuentes renovables intermitentes. El enfoque propuesto emplea series históricas con resolución media horaria de demanda eléctrica, generación eólica y solar, aplicando una técnica de convolución discreta para combinar sus distribuciones de probabilidad respectivas.A diferencia de métodos convencionales, esta metodología permite estimar reservas diferenciadas según la hora del día y el tipo de día (laborable o no laborable), mejorando la precisión y eficiencia del sistema. La validez del método fue evaluada utilizando datos del sistema eléctrico peruano, demostrando su escalabilidad y adaptabilidad a otroscontextos. Los resultados evidencian mejoras significativas en el dimensionamiento y distribución de la RSF, lo que contribuye a una operación segura, eficiente y confiable de los SEP modernos.Universidad de San Martín de Porres2025-08-22info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionapplication/pdfhttps://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161Campus; Vol. 30 No. 39 (2025): Campus XXXIXCampus; Vol. 30 Núm. 39 (2025): Campus XXXIXCampus; v. 30 n. 39 (2025): Campus XXXIX2523-18201812-6049reponame:Revistas - Universidad de San Martín de Porresinstname:Universidad de San Martín de Porresinstacron:USMPspahttps://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161/3996Derechos de autor 2025 Javier Aracayohttps://creativecommons.org/licenses/by/4.0info:eu-repo/semantics/openAccessoai:revistas.usmp.edu.pe:article/31612025-08-25T14:21:35Z |
| dc.title.none.fl_str_mv |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation Un método probabilístico dinámico para determinarla reserva para regulación secundaria de frecuencia ensistemas eléctricos de potencia con alta integraciónde generación eólica y solar |
| title |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| spellingShingle |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation Aracayo, Javier Wind and Solar Generation Dynamic Probabilistic Method Convolution Secondary Frequency Regulation Electric Power System Demand Generación Eólica y Solar Método Probabilístico Dinámico Convolución Regulación Secundaria de Frecuencia Sistema Eléctrico de Potencia Demanda |
| title_short |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| title_full |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| title_fullStr |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| title_full_unstemmed |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| title_sort |
A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation |
| dc.creator.none.fl_str_mv |
Aracayo, Javier |
| author |
Aracayo, Javier |
| author_facet |
Aracayo, Javier |
| author_role |
author |
| dc.subject.none.fl_str_mv |
Wind and Solar Generation Dynamic Probabilistic Method Convolution Secondary Frequency Regulation Electric Power System Demand Generación Eólica y Solar Método Probabilístico Dinámico Convolución Regulación Secundaria de Frecuencia Sistema Eléctrico de Potencia Demanda |
| topic |
Wind and Solar Generation Dynamic Probabilistic Method Convolution Secondary Frequency Regulation Electric Power System Demand Generación Eólica y Solar Método Probabilístico Dinámico Convolución Regulación Secundaria de Frecuencia Sistema Eléctrico de Potencia Demanda |
| description |
The rapid growth of wind and solar generation has introduced significant variability and uncertainty into the operation of electric power systems (SEP), challenging traditional methods for sizing operating reserves. This article presents a dynamic probabilistic method based on the convolution of probability distribution functions, aimed at accurately estimating the reserve required for Secondary Frequency Regulation (RSF) in contexts with high penetration of intermittent renewable sources. The proposed approach employs historical time series data with halfhour resolution for electricity demand, wind generation, and solar generation, applying a discrete convolution technique to combine their respectiveprobability distributions. Unlike conventional methods, this methodology allows for differentiated reserve estimation according to the hour of the dayand the type of day (weekday or non-weekday), enhancing the precision and operational efficiency of the system. The validity of the method was assessed using data from the Peruvian power system, demonstrating its scalability and adaptability to other systems with increasing renewable energy participation.The results show significant improvements in the sizing and allocation of SFR, contributing to a more secure, efficient, and reliable operation of modernpower systems. |
| publishDate |
2025 |
| dc.date.none.fl_str_mv |
2025-08-22 |
| dc.type.none.fl_str_mv |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| format |
article |
| status_str |
publishedVersion |
| dc.identifier.none.fl_str_mv |
https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161 |
| url |
https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161 |
| dc.language.none.fl_str_mv |
spa |
| language |
spa |
| dc.relation.none.fl_str_mv |
https://portalrevistas.aulavirtualusmp.pe/index.php/rc/article/view/3161/3996 |
| dc.rights.none.fl_str_mv |
Derechos de autor 2025 Javier Aracayo https://creativecommons.org/licenses/by/4.0 info:eu-repo/semantics/openAccess |
| rights_invalid_str_mv |
Derechos de autor 2025 Javier Aracayo https://creativecommons.org/licenses/by/4.0 |
| eu_rights_str_mv |
openAccess |
| dc.format.none.fl_str_mv |
application/pdf |
| dc.publisher.none.fl_str_mv |
Universidad de San Martín de Porres |
| publisher.none.fl_str_mv |
Universidad de San Martín de Porres |
| dc.source.none.fl_str_mv |
Campus; Vol. 30 No. 39 (2025): Campus XXXIX Campus; Vol. 30 Núm. 39 (2025): Campus XXXIX Campus; v. 30 n. 39 (2025): Campus XXXIX 2523-1820 1812-6049 reponame:Revistas - Universidad de San Martín de Porres instname:Universidad de San Martín de Porres instacron:USMP |
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Universidad de San Martín de Porres |
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USMP |
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USMP |
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Revistas - Universidad de San Martín de Porres |
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Revistas - Universidad de San Martín de Porres |
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Nota importante:
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).
La información contenida en este registro es de entera responsabilidad de la institución que gestiona el repositorio institucional donde esta contenido este documento o set de datos. El CONCYTEC no se hace responsable por los contenidos (publicaciones y/o datos) accesibles a través del Repositorio Nacional Digital de Ciencia, Tecnología e Innovación de Acceso Abierto (ALICIA).