A dynamic probabilistic method to determine the reserve forsecondary frequency regulation in electric power systems with highintegration of wind and solar generation

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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...

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Detalles Bibliográficos
Autor: Aracayo, Javier
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
Descripción
Sumario: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.
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