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Phase-selection algorithms to minimize cost and imbalance in U.S. synthetic distribution systems

F. Postigo, C. Mateo, T. Gómez, F. de Cuadra, P. Dueñas, T. Elgindy, B.M. Hodge, B. Palmintier, V. Krishnan

The increasing penetration of distributed energy resources (DERs) has driven a push toward new algorithms and tools for distribution system operation and planning; however, there is a lack of publicly available electrical distribution test systems at the large scale-multi-feeder, multi-substation-which are required for realistically evaluating the performance and scalability of these new developments. This paper presents a Reference Network Model (RNM) aimed to plan large-scale, U.S.-style, synthetic distribution systems. Special emphasis is placed on two algorithms that allow multi-phase feeder design: (1) a method to select the most suitable number of phases for each section considering the connected customers, and (2) a method to assign phases to the users to provide near-balanced phasing while maintaining realistic levels of imbalance. The performance of the developed algorithms is verified by comparing the obtained system designs with the original IEEE 8,500-node test feeder and the Electric Power Research Institute (EPRI) J1 feeder.


Palabras clave: Power distribution; System planning; Reference Network Model; Representative networks; Synthetic networks; Phase imbalance


International Journal of Electrical Power & Energy Systems. Volumen: 120 Número: 106042 Páginas: 1-9

Índice de impacto JCR y cuartil WoS: 4.418 - Q1 (2018)

Referencia DOI: DOI icon 10.1016/j.ijepes.2020.106042    

Publicado en papel: Septiembre 2020. Publicado on-line: Abril 2020.



Cita:
F. Postigo, C. Mateo, T. Gómez, F. de Cuadra, P. Dueñas, T. Elgindy, B.M. Hodge, B. Palmintier, V. Krishnan. Phase-selection algorithms to minimize cost and imbalance in U.S. synthetic distribution systems. International Journal of Electrical Power & Energy Systems. vol. 120, no. 106042, pp. 1-9, Septiembre 2020. [Online: Abril 2020]


    Líneas de investigación:
  • Redes eléctricas representativas y aplicaciones
  • Redes inteligentes
  • Planificación y operación de recursos energéticos distribuidos

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