DOI QR코드

DOI QR Code

A Study on Predicting Installation Scale of Photovoltaic Panels and Hydrogen Fuel Storage Facilities to Achieve Net Zero Carbon Emissions Exploiting Idle Sites of Military Bases

군부대 유휴부지를 활용한 탄소 순 배출량 제로 달성을 위한 태양광 패널 및 수소 연료 저장시설의 설치 규모 예측

  • Donghak Moon (Korea Army Academy at Yeongcheon, Chemecal and Environmental Sciences) ;
  • Jiyong Heo (Korea Army Academy at Yeongcheon, Civil Engineering)
  • 문동학 (육군3사관학교 화학환경과학과) ;
  • 허지용 (육군3사관학교 건설공학과)
  • Received : 2023.10.17
  • Accepted : 2024.01.10
  • Published : 2024.02.05

Abstract

In this study, the scale of renewable photovoltaic(PV) panels and hydrogen fuel storage facilities required to achieve "net zero carbon emissions" in military facilities were predicted based on actual electricity consumption. It was set up to expect the appropriate installation size of PV panel and hydrogen fuel storage facility for achieving carbon neutrality, limited to the electricity consumption in the public sector, including national defense and social security administration in Yeongcheon. The experimental results of this paper are largely composed of two parts. First, representative meteorological factors were considered to predict solar power generation in the Yeongcheon area, and solar power generation was estimated through a multiple regression model using deep learning techniques. Second, the size of solar power generation facilities and hydrogen storage facilities in military bases was estimated with the amount of solar power generation and electricity consumption. As a result of this analysis, it was calculated that a site of 155.76×104 m2 for PV panels was needed and a facility capable of storing 27,657 kg of hydrogen gas was required. Through these results, it is meaningful to demonstrated the prospect that military units can lead the achievement of "carbon net zero 2050" by using PV panels and hydrogen fuel storage facilities on idle sites of military bases.

Keywords

Acknowledgement

이 논문은 육군3사관학교 부설 충성대연구소 2024년도 논문게재비 지원을 받았음.

References

  1. Song Eunju, "Political and Cultural Significance of Geoengineering in the Anthropocene in Snopiercer and Interstella," TRANS-HUMANITIES, Vol. 15, No. 1, pp. 207-236, 2022. 
  2. Zixuan Wang, Zhi Liu, Linhao Fan, Qing Du, and Kui Jiao., "Application progress of small-scale proton exchange memerane fuel cell," Energy Reviews, Volume 2 100017, pp. 1-12, 2023.  https://doi.org/10.1016/j.enrev.2023.100017
  3. Min Hwan Lee, "Fuel Economy," Maxmedia, Sungnam Gyeonggi-do, pp. 110-111, 2022. 
  4. Airlines, "70 years of IATA : we trace aviation's environmental commitment," (ENVIRONMENT/GLOBAL/26 Ausgust 2015), https://airlines.iata.org/2015/08/26/70-years-iata-we-trace-aviations-environmental-commitment, IATA, 2015. 
  5. EPA, "Fast Facts, US Transportation Sector Greenhouse Gas Emissions," https://www.epa.gov/greenvehicles/fast-facts-transportation-greenhouse-gas-emissions, EPA, 2021. 
  6. P. Dhanalakshmi, V. Venkatesh and P. S. Ranjit., "Application of Machine Learning in Multi-Directional Model to Follow Solar Energy Using Photo Sensor Matrix," Hindawi International Journal of Photoenergy, Volume 2022, pp. 1-9, 2022.  https://doi.org/10.1155/2022/5756610
  7. A. Gensler, J. Henze, B. Sick and N. Raabe., "Deep learning for solar power forecasting - An approach using autoencoder and LSTM neural networks," IEEE, 2016 IEEE International Conference on Systems, Man, Cybern. (SMC), pp. 2858-2865, 2016. 
  8. Gowoon Kang, Joowon Park, Hyosik Yang, "A Study on the Prediction of Solar Photovoltaic Power Generation using Multiple-linear Regression," KICS, 19A, 238, pp. 556-557, 2022. 
  9. Kim Beob-Jeon, Park Jae-Wan, Yoon Jong-Ho and Shin U-Cheul, "The Development of Performance Evaluation Program of Building Integrated Photovoltaic System," KIEAE Journal, Vol. 15, No. 4, pp. 85-90, 2015.  https://doi.org/10.12813/kieae.2015.15.4.085
  10. Heo Jae, Park Bumsoo, Kim Byungil and Han SangUk, "Multiple Linear Regression Analysis of PV Power Forecasting for Evaluation and Selection of Suitable PV Sites," KJCEM, Vol. 20, No. 6, pp. 126-131, 2019. 
  11. Keunho Lee, Heung-gu Son and Sahm Kim, "A study on solar energy forecasting based on time series models," The Korean Journal of Applied Statistics, Vol. 31 No. 1, pp. 139-153, 2018.  https://doi.org/10.5351/KJAS.2018.31.1.139
  12. Zuttel. A, "hydrogen storage methods," NATURWISSENSCHAFTEN, 91(4). pp. 157-172, 2004. https://doi.org/10.1007/s00114-004-0516-x