Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/75757
Título
AC/DC optimal power flow and techno-economic assessment for hybrid microgrids: TIGON CEDER demonstrator
Autor
Año del Documento
2024
Editorial
Frontiers Media SA
Descripción
Producción Científica
Documento Fuente
Frontiers in Energy Research, Agosto 2024, vol. 12, p. 1-14
Abstract
In recent years, the interest in electric direct current (DC) technologies (such as converters, batteries, and electric vehicles) has increased due to their potential in energy efficiency and sustainability. However, the vast majority of electric systems and networks are based on alternating current (AC) as they also have certain advantages regarding cost-effective transport and robustness. In this paper, an AC/DC optimal power flow method for hybrid microgrids and several key performance indicators (KPIs) for its techno-economic assessment are presented. The combination of both calculations allows users to determine the viability of their hybrid microgrids. AC/DC networks have been modeled considering their most common elements. For the power flow method, polynomial optimization is formulated considering four different objective functions: the minimization of energy losses, voltage deviation, and operational costs and the maximization of the microgrid generation. The power flow method and the techno–economic analysis are implemented in Python and validated in the Centro de Desarrollo de Energías Renovables (CEDER) demonstrator for TIGON. The results show that the calculated power flow variables and those measured at CEDER are practically the same. In addition, the KPIs are obtained and compared for four operating scenarios: baseline, no battery, battery flexibility, and virtual battery (VB) flexibility. The last scenario results in the most profitable option.
Materias Unesco
3306 Ingeniería y Tecnología Eléctricas
Palabras Clave
AC/DC optimal power flow
hybrid microgrids
key performance indicators
polynomial optimization
techno-economic assessment
Python
ISSN
2296-598X
Revisión por pares
SI
Patrocinador
This research received funding from the European Union’s Horizon 2020 TIGON project under grant agreement no. 957769
Version del Editor
Idioma
eng
Tipo de versión
info:eu-repo/semantics/publishedVersion
Derechos
openAccess
Collections
Files in this item
