Machine Learning-based hydrogen charging station energy demand prediction model

MinWoo Hwang; Yerim Ha; Sanguk Park

Machine Learning-based hydrogen charging station energy demand prediction model

MinWoo Hwang, Yerim Ha, Sanguk Park, Journal of Internet Computing and Services, Vol. 24, No. 2, pp. 47-56, Apr. 2023

10.7472/jksii.2023.24.2.47, Full Text:

Keywords: Smart hydrogen energy, carbon neutrality, energy demand forecasting, Machine Learning, hydrogen charging station

Abstract

Hydrogen energy is an eco-friendly energy that produces heat and electricity with high energy efficiency and does not emit harmful substances such as greenhouse gases and fine dust. In particular, smart hydrogen energy is an economical, sustainable, and safe future smart hydrogen energy service, which means a service that stably operates based on 'data' by digitally integrating hydrogen energy infrastructure. In this paper, in order to implement a data-based hydrogen charging station demand forecasting model, three hydrogen charging stations (Chuncheon, Sokcho, Pyeongchang) installed in Gangwon-do were selected, supply and demand data of hydrogen charging stations were secured, and 7 machine learning and deep learning algorithms were used. was selected to learn a model with a total of 27 types of input data (weather data + demand for hydrogen charging stations), and the model was evaluated with root mean square error (RMSE). Through this, this paper proposes a machine learning-based hydrogen charging station energy demand prediction model for optimal hydrogen energy supply and demand.

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Cite this article

[APA Style]

Hwang, M., Ha, Y., & Park, S. (2023). Machine Learning-based hydrogen charging station energy demand prediction model. Journal of Internet Computing and Services, 24(2), 47-56. DOI: 10.7472/jksii.2023.24.2.47.

[IEEE Style]

M. Hwang, Y. Ha, S. Park, "Machine Learning-based hydrogen charging station energy demand prediction model," Journal of Internet Computing and Services, vol. 24, no. 2, pp. 47-56, 2023. DOI: 10.7472/jksii.2023.24.2.47.

[ACM Style]

MinWoo Hwang, Yerim Ha, and Sanguk Park. 2023. Machine Learning-based hydrogen charging station energy demand prediction model. Journal of Internet Computing and Services, 24, 2, (2023), 47-56. DOI: 10.7472/jksii.2023.24.2.47.