Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches

Revisión de estrategias de modelado de la demanda de carga para vehículos eléctricos: una comparación de enfoques grid-to-vehicle probabilísticos

Autores/as

  • Carlos David Zuluaga Ríos Institución Universitaria Pascual Bravo https://orcid.org/0000-0002-1196-2227
  • Daniel Felipe Florián Ceballos Institución Universitaria Pascual Bravo
  • Miguel Ángel Rojo Yepes Institución Universitaria Pascual Bravo
  • Sergio Danilo Saldarriaga Zuluaga Institución Universitaria Pascual Bravo https://orcid.org/0000-0002-9134-8576

Palabras clave:

demanda de carga de vehículos eléctricos, simulación de Monte Carlo, modelado probabilístico (es).

Palabras clave:

electric vehicle charging demand, Monte Carlo simulation, probabilistic modeling (en).

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Resumen (en)

Objective: In this paper, we review different approaches to how the penetration of electric vehicles (EV) can be modeled in power networks. We also evaluate and compare experimentally the performance of three probabilistic electric vehicle charging load approaches considering four levels of penetration of EV.

Methodology:  We carry out a detailed search of the state-of-the-art in charging load modeling strategies for electric vehicles, where the most representative works on this subject were compiled. A probabilistic model based on Monte Carlo Simulation was proposed and two more methods were implemented. These models take into account the departure time of electric vehicles, the arrival time and the plug-in time, which were conceived as random variables.  

Results:  Histograms of the demand for charging of electric vehicles were obtained for the three models contemplated. Additionally, a similarity metric was calculated to know the distribution that best fits the data of each model. The above was done considering 20, 200, 2000 and 20,000 electric vehicles on average. The results show that if there are a low penetration of electric vehicles, it is possible to model the EV charging demand using a gamma distribution. Otherwise, it is recommended to use a Gaussian or Lognormal distribution if you have a high VE penetration.

Conclusions: A review of the state of the art of the modeling of electric vehicles under a G2V approach was presented, where three groups are identified: the deterministic approaches, methods that deal with uncertainty and variability, and finally data driven methods were also identified. Additionally, we observed that the EVCP model 3 and the gamma distribution can be appropriate for modeling the penetration of EVs in probabilistic load flow analysis or for stochastic planning studies for active distribution networks.

Financing: Institución Universitaria Pascual Bravo

Resumen (es)

Objetivo:  En este artículo se revisaron diferentes enfoques sobre cómo modelar la penetración de los vehículos eléctricos (EV) en los sistemas eléctricos de potencia. También se evalúa y compara experimentalmente el desempeño de tres enfoques probabilísticos de demanda de carga de vehículos eléctrico considerando cuatro niveles de penetración de EV.

Metodología: Se realiza una búsqueda detallada del estado del arte de estrategias de modelado de carga de carga para vehículos eléctricos, donde se recopilaron los trabajos más representativos sobre este tema. Se propuso un modelo probabilístico basado en la simulación de Monte Carlo y se implementaron dos métodos más. Estos modelos tienen en cuenta la hora de salida de los vehículos eléctricos, la hora de llegada y la hora que se conectan a la red. Estas variables fueron concebidas como variables aleatorias.

Resultados: Se obtuvieron histogramas de la demanda de carga de los vehículos eléctricos para los tres modelos contemplados. Adicionalmente, se calculó una métrica de similaridad para conocer la distribución que mejor se ajusta a los datos de cada modelo. Lo anterior, se realizó considerando 20, 200, 2000 y 20000 vehículos eléctricos en promedio. Si se tiene una baja penetración de vehículos eléctricos es posible modelar la demanda de estos usando una distribución gamma. De lo contrario, se recomienda usar una distribución Gaussiana o Lognormal si se tiene una alta penetración de VE.

Conclusiones: Se presentó una revisión del estado del arte en el modelado de vehículos eléctricos bajo un enfoque G2V, donde se identificaron tres grupos: los enfoques deterministas, los métodos que tratan la incertidumbre y la variabilidad y, finalmente, se identificaron los métodos basados ​​en datos. Adicionalmente, observamos que el modelo EVCP 3 y la distribución gamma pueden ser apropiados para modelar la penetración de vehículos eléctricos en análisis de flujo de carga probabilístico o para estudios de planeamiento estocástico en redes de distribución activas.

Financiamiento: Institución Universitaria Pascual Bravo

Biografía del autor/a

Carlos David Zuluaga Ríos, Institución Universitaria Pascual Bravo

Doctorado en Ingeniería, Maestría en Ingeniería Eléctrica, Ingeniero Eléctrico. Profesor, Departamento de Ingeniería, área de Ingeniería Eléctrica, Institución Universitaria Pascual Bravo. Medellín, Colombia.

Daniel Felipe Florián Ceballos, Institución Universitaria Pascual Bravo

Estudiante de Ingeniería Eléctrica. Departamento de Ingeniería, área de Ingeniería Eléctrica, Institución Universitaria Pascual Bravo. Medellín, Colombia

Miguel Ángel Rojo Yepes, Institución Universitaria Pascual Bravo

Estudiante de Ingeniería Eléctrica. Departamento de Ingeniería, área de Ingeniería Eléctrica, Institución Universitaria Pascual Bravo. Medellín, Colombia

Sergio Danilo Saldarriaga Zuluaga, Institución Universitaria Pascual Bravo

Doctorado en Ingeniería, Maestría en Ingeniería Eléctrica, ingeniero eléctrico. Profesor, Facultad de Ingeniería, Departamento de Ingeniería Eléctrica, Institución Universitaria Pascual Bravo. Medellín, Colombia.

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Cómo citar

APA

Zuluaga Ríos, C. D., Florián Ceballos, D. F. ., Rojo Yepes, M. Ángel ., & Saldarriaga Zuluaga, S. D. . (2021). Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches . Tecnura, 25(70). https://doi.org/10.14483/22487638.18657

ACM

[1]
Zuluaga Ríos, C.D., Florián Ceballos, D.F. , Rojo Yepes, M. Ángel . y Saldarriaga Zuluaga, S.D. 2021. Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches . Tecnura. 25, 70 (nov. 2021). DOI:https://doi.org/10.14483/22487638.18657.

ACS

(1)
Zuluaga Ríos, C. D.; Florián Ceballos, D. F. .; Rojo Yepes, M. Ángel .; Saldarriaga Zuluaga, S. D. . Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches . Tecnura 2021, 25.

ABNT

ZULUAGA RÍOS, C. D.; FLORIÁN CEBALLOS, D. F. .; ROJO YEPES, M. Ángel .; SALDARRIAGA ZULUAGA, S. D. . Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches . Tecnura, [S. l.], v. 25, n. 70, 2021. DOI: 10.14483/22487638.18657. Disponível em: https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/18657. Acesso em: 20 ene. 2022.

Chicago

Zuluaga Ríos, Carlos David, Daniel Felipe Florián Ceballos, Miguel Ángel Rojo Yepes, y Sergio Danilo Saldarriaga Zuluaga. 2021. «Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches ». Tecnura 25 (70). https://doi.org/10.14483/22487638.18657.

Harvard

Zuluaga Ríos, C. D., Florián Ceballos, D. F. ., Rojo Yepes, M. Ángel . y Saldarriaga Zuluaga, S. D. . (2021) «Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches », Tecnura, 25(70). doi: 10.14483/22487638.18657.

IEEE

[1]
C. D. Zuluaga Ríos, D. F. . Florián Ceballos, M. Ángel . Rojo Yepes, y S. D. . Saldarriaga Zuluaga, «Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches », Tecnura, vol. 25, n.º 70, nov. 2021.

MLA

Zuluaga Ríos, C. D., D. F. . Florián Ceballos, M. Ángel . Rojo Yepes, y S. D. . Saldarriaga Zuluaga. «Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches ». Tecnura, vol. 25, n.º 70, noviembre de 2021, doi:10.14483/22487638.18657.

Turabian

Zuluaga Ríos, Carlos David, Daniel Felipe Florián Ceballos, Miguel Ángel Rojo Yepes, y Sergio Danilo Saldarriaga Zuluaga. «Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches ». Tecnura 25, no. 70 (noviembre 30, 2021). Accedido enero 20, 2022. https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/18657.

Vancouver

1.
Zuluaga Ríos CD, Florián Ceballos DF, Rojo Yepes M Ángel, Saldarriaga Zuluaga SD. Review of Charging Load Modeling Strategies for Electric Vehicles: a Comparison of Grid-to-Vehicle Probabilistic Approaches . Tecnura [Internet]. 30 de noviembre de 2021 [citado 20 de enero de 2022];25(70). Disponible en: https://revistas.udistrital.edu.co/index.php/Tecnura/article/view/18657

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