A novel stochastic framework for optimal scheduling of smart cities as an energy hub

M. Shokri, T. Niknam, M. Mohammadi, M. Dehghani, P. Siano, K. Ouahada, M. Sarvarizadeh

IET Generation Transmission & Distribution Vol. 18, nº. 14, pp. 2421 - 2434

Resumen:

Smart cities consist of various energy systems and services that must be optimally scheduled to improve energy efficiency and reduce operation costs. The smart city layout comprises a power distribution system, a thermal energy system, a water system, and the private and public transportation systems. Additionally, several new technologies such as reconfiguration, regenerative braking energy of the metro, etc. are considered. This study is one of the first to consider all these technologies together in a smart city. The proposed power distribution system is a grid-connected hybrid AC–DC microgrid. The biogeography-based optimization algorithm was utilized to seek the best solution for scheduling micro-turbines, fuel cells, heat pumps, desalination units, energy storage systems, AC–DC converters, purchasing power from the upstream, distributed energy resources, and transferring power amongst electric vehicle parking stations and metro for the next day. Also, the reduced unscented transformation layout was used to capture the system's uncertainty. The suggested layout is implemented on an enhanced IEEE 33-bus test system to show the efficiency of the suggested method. The results show that costs and environmental pollution are reduced. By comparing the proposed smart city with other studies, the efficiency and completeness of the proposed smart city are shown.

Resumen divulgativo:

Las ciudades inteligentes mejoran la eficiencia y reducen costes integrando la distribución eléctrica, la energía térmica, los sistemas de agua y el transporte. Este estudio combina tecnologías como la reconfiguración y el frenado regenerativo en una microrred híbrida CA-CC. Utilizando un algoritmo de optimización basado en la biogeografía, programa los recursos de forma óptima. Los resultados muestran una reducción de los costes y la contaminación, lo que demuestra la eficacia del método.

Palabras Clave: Smart cities, Energy hub, BBO algorithm, Microgrid, Hybrid AC-DC

Índice de impacto JCR y cuartil WoS: 2,000 - Q3 (2023)

Referencia DOI: https://doi.org/10.1049/gtd2.13202

Publicado en papel: Julio 2024.

Publicado on-line: Junio 2024.

Cita:
M. Shokri, T. Niknam, M. Mohammadi, M. Dehghani, P. Siano, K. Ouahada, M. Sarvarizadeh, A novel stochastic framework for optimal scheduling of smart cities as an energy hub. IET Generation Transmission & Distribution. Vol. 18, nº. 14, pp. 2421 - 2434, Julio 2024. [Online: Junio 2024]