Site selection of Antarctic Research Stations in aspect of required optimum hybrid renewable system capacity

Abstract

The population of Antarctica consists of scientific research personnel. The number of residents ranges from about 1,100 in the winter to about 4,400 in the summer and up to 1,000 additional personnel in the nearby waters. Even in summer, Antarctica's sub-zero temperature increases the energy consumption of buildings for heating purposes. At the same time, the absence of a grid system necessitates the use of off-grid fossil-based or renewable energy systems. Considering the natural environment and building conditions in the studies, the multiple evaluation of the ground process for research stations is grouped into four main criteria: scientific research, environment, logistical support and topography. In these studies, the capacity of the renewable energy system requirement was not examined. For this reason, in this study, the capacities of the optimum hybrid renewable energy systems in 16 locations selected from different regions of Antarctica were compared. In the study, typical meteorological climate data of 15 locations were obtained. The daily energy demand is obtained by calculating the daily electricity consumption of the electrical devices and heating system that can be used. Results of this study shows that according to purpose of the site, many locations that meets the requirements may exist with extremely different energy demands. In site selection, first the possile locations that supply the requirements should be determined, than energy demands and required systems should be compared.

Keywords

• Cold climate
• Electricity production
• Renewable system
• Optimization

References

1. [1] Yavaşoğlu H, Karaman H, Özsoy B, Bilgi S, Tutak B, Gengeç AG, Oktar Ö, Yirmibeşoğlu S. Site selection of the Turkish Antarctic Research station using Analytic Hierarchy Process. Polar Science 2019; 22: 100473.
2. [2] Xiaoping P, Haiyan L, Xi Z. Selecting suitable sites for an Antarctic research station: a case for a new Chinese research station. Antarctic Science 2014; 26(5): 479–490.
3. [3] Trubetskoy S. Antarktika nüfusu, 2019. Available: https://sashamaps.net/docs/maps/population-of-antarctica/.
4. [4] Lonin S, Rios-Angulo WA, Coronado J. Swell Conditions at Potential Sites for the Colombian Antarctic Research Station. Sustainability 2022; 14(4): 2318.
5. [5] Lucci JJ, Alegre M, Vigna L. Renewables in Antarctica: an assessment of progress to decarbonize the energy matrix of research facilities. Antarctic Science 2022; 34(5): 374-388.
6. [6] Vigna L. Renewable Energy in Antarctic Research Facilities. 2022. Available: https://public.flourish.studio/visualisation/5888942/.
7. [7] Boccaletti C, Felice PD, Santini E. Integration of renewable power systems in an Antarctic Research Station. Renewable Energy 2014; 62: 582-591.
8. [8] Christo TM, Fardin JF, Simonetti DSL, Encarnação LF, Alvarez CE. Design and analysis of hybrid energy systems: The Brazilian Antarctic Station case. Renewable Energy 2016; 88: 236-246.

9. [9] Dou Y, Zuo G, Chang X, ChenY. A Study of a Standalone Renewable Energy System of the Chinese Zhongshan Station in Antarctica. Applied Sciences 2019; 9: 1968.
10. [10] Bockelmann F, Dreier AK, Zimmermann J, Peter M. Renewable energy in Antarctica - Photovoltaic for Neumayer Station III. Solar Energy Advances 2022; 2: 100026.
11. [11] Crawley D, Lawrie L. Climate.OneBuilding.Org, 2022. Available: http://climate.onebuilding.org/default.html.
12. [12] CW. CW 675 Wp, 2023. Available: https://cw-enerji.com/tr/urun/cw-enerji-675-wp-132pmbs-m12-hc-mb- gunes-paneli-1289.html.
13. [13] SD Wind Energy. SD3, 2023. Available: https://sd-windenergy.com/small-wind-turbines/sd3-3kw-wind-turbine/.
14. [14] Al-Ghussain L, Taylan O, Baker DK. An investigation of optimum PV and wind energy system capacities for alternate short and long-term energy storage sizing methodologies. International Journal of Energy Research 2019; 43(1): 204-218.
15. [15] Tazay A. Techno-Economic Feasibility Analysis of a Hybrid Renewable Energy Supply Options for University Buildings in Saudi Arabia. Open Engineering 2021; 11(1): 39-55.
16. [16] Li J, Wei W, Xiang J. A simple sizing algorithm for stand-alone PV/wind/battery hybrid microgrids. Energies 2012; 5(12): 5307-5323.
17. [17] Belmili H, Haddadi M, Bacha S, Almi MF, Bendib B. Sizing stand-alone photovoltaic–wind hybrid system: Techno-economic analysis and optimization. Renewable and Sustainable Energy Reviews 2014; 30: 821-832.
18. [18] Haidar AM, Fakhar A, Helwig A. Sustainable energy planning for cost minimization of autonomous hybrid microgrid using combined multi-objective optimization algorithm. Sustainable Cities and Society 2020; 62: 102391.
19. [19] Kaabeche A, Ibtiouen R. Techno-economic optimization of hybrid photovoltaic/wind/diesel/battery generation in a stand-alone power system. Solar Energy 2014; 103: 171-182.
20. [20] Jakhrani AQ, Rigit ARH, Othman AK, Samo SR, Kamboh SA. Estimation of carbon footprints from diesel generator emissions. International Conference on Green and Ubiquitous Technology, Bandung, Indonesia, 2012.
21. [21] Tomov P. Multilayer Perceptron Fast Prototyping with Differential Evolution and Particle Swarm Optimization in LibreOffice Calc. Bulgarian Academy of Sciences Problems of Engineering Cybernetics and Robotics 2021; 75: 5-14.
22. [22] MacEachern C, Yıldız I. Wind Energy, Comprehensive Energy Systems, Elsevier, 2018; 665-701.