Audit Energi pada Data Center Kampus untuk Efisiensi Energi Berbasis Digital Twin

https://doi.org/10.5614/joki.2023.15.1.6

Penulis

  • Rizal Faris Mustaram Teknik Fisika Institut Teknologi Bandung
  • Teguh Solavide Gulo Teknik Fisika Institut Teknologi Bandung
  • Edi Leksono Teknik Fisika Institut Teknologi Bandung
  • Justin Pradipta Teknik Fisika Institut Teknologi Bandung

Kata Kunci:

digital twin, data center, HVAC, kesetimbangan panas, manajemen energi

Abstrak

Penelitian dikembangkan menggunakan teknik digital twin untuk membuat prediksi beban termal melalui data real time pada sistem HVAC di data center. Digitalisasi sistem perangkat fisik dilakukan dengan menggunakan teknologi IoT (Internet of Things), melalui teknologi IoT ini ruang digital dibuat untuk merepresentasikan model prediksi. Membuat instrumentasi akuisisi data dan sistem pemantauan real time melalui teknik IoT serta analisis kinerja sisem pendingin data center. Tujuan yang hendak dicapai dalam penelitian ini adalah mendapatkan prediksi beban termal sistem energi data center, kemudian dianalisis menggunakan metode heat balance agar dapat diketahui rasio beban termal terhadap kinerja (kapasitas pendinginan) perangkat pendingin data center yang ada. Hal ini dilakukan agar dapat mengetahui potensi penghematan energi listrik. Hasil prediksi beban termal didapat nilai rata-rata 30,66 kW/jam untuk tanggal 25 Oktober 2022 dan 29,88 kW/jam untuk tanggal 26 Oktober 2022. Sehingga nilai kesetimbangan beban panas (heat balance) terhadap kapasitas pendinginan nominal perangkat pendingin terpasang yaitu 40, 95 % untuk PAC 1 dan 49,21 % untuk PAC 2.

Referensi

E. Oró, V. Depoorter, A. Garcia and J. Salom, “Energy Efficiency and Renewable Energy Integration in Data Centres. Strategies and Modelling Review”, Renewable and Sustainable Energy Reviews, Vol. 42, pp. 429-445, 2015.

B. Whitehead, D. Andrews, A. Shah and G. Maidment “Assessing the Environmental Impact of Data Centres Part 1: Background, Energy Use and Metrics”, Building and Environment, Vol 82, pp 151-159, 2014.

M. Dayarathna, Y. Wen and R. Fan, “Data Center Energy Consumption Modeling: A Survey”, IEEE Communications Surveys & Tutorials, Vol. 18, 2016.

https://www.iea.org/data-and-statistics/charts/global-data-centre-energy-demand-by-data-centre-type-2010-2022 (accessed: 16 March 2023) .

M. Koot, and F. Wijnhoven, “Usage Impact on Data Center Electricity Needs: A System Dynamic Forecasting Model,” Applied Energy, vol 291, 116798, 2021.

B. Hadid, S. Lecoeuche, D. Gille, and C. Labarre, “Energy Efficiency of Data Centers: A Data-Driven Model-Based Approach”, IEEE International Energy Conference (ENERGYCON), pp. 1-6, 2016.

Y. Weiping, Z. Wang, Y. Xue, L. Guo and L. Xu, “A Combined Neural and Genetic Algorithm Model for Data Center Temperature Control”, Science and Technology Program of State Grid, 2017.

R. Snijders, P. Pileggi, J. Broekhuijsen, J. Verriet, M. Wiering and K. Kok, "Machine Learning for Digital Twins to Predict Responsiveness of Cyber-Physical Energy Systems," 8th Workshop on Modeling and Simulation of Cyber-Physical Energy Systems, Sydney, NSW, Australia,pp. 1-6, 2020.

D. Jones, C. Snider, A. Nassehi, J. Yon, and B. Hicks, “Characterizing the Digital Twin: A Systematic Literature Review,” CIRP J. Manuf. Sci. Techno.l, vol. 29, pp 36-52, 2020.

A. Fuller, Z. Fan, C. Day, and C. Barlow, “Digital Twin: Enabling Technologies, Challenges and Open Research,” IEEE Access, vol. 8, pp. 108952-108971, 2020.

A. Rasheed, O. San and T. Kvamsdal, "Digital Twin: Values, Challenges and Enablers from a Modeling Perspective," IEEE Access, vol. 8, pp. 21980-22012, 2020.

R. Stark and T. Damerau, “Digital Twin”. in CIRP Encyclopedia of Production Engineering , Chatti, S., Tolio, T. (eds), Springer, pp. 1–8, 2019.

X. Xie, Q. Lu, A.K. Parlikad, and J. Schooling, “Digital Twin Enabled Asset Anomaly Detection for Building Facility Management,” IFAC PaperOnLine, vol.53(3), pp. 380-385, 2020.

E. Vanderhorn and S. Mahadevan, “Digital Twin: Generalization, Characterization, and Implementation,” Decision Support Systems, Vol. 145, no. 113524, pp. 0167-9236, 2021.

D. Jones, C. Snider, A. Nassehi, J. Yon, and B. Hicks, “Characterizing the Digital Twin: A Systematic Literature Review,” CIRP Journal of Manufacturing Science and Technology, vol. 29, pp. 36-52, 2020.

W. Kritzinger, M. Karner, G. Traar, J. Henjes, and W. Sihn, “Digital Twin in Manufacturing : A Categorical Literature Review And Classification,” IFAC-PapersOnLine, vol. 51, pp. 1016-1022, 2018.

T. Bergs, S. Gierlings, T. Auerbach, A. Klink, D. Schraknepper, and T. Augspurger, “The Concept of Digital Twin and Digital Shadow in Manufacturing,” Procedia CIRP, vol. 101, pp. 81-84, 2021.

M. Grieves and J. Vickers, “Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems,” in Transdisciplinary Perspectives on Complex Systems : Springer, pp. 85–113, 2017.

Diterbitkan

2023-05-06

Cara Mengutip

[1]
R. F. Mustaram, T. S. Gulo, E. Leksono, dan J. Pradipta, “Audit Energi pada Data Center Kampus untuk Efisiensi Energi Berbasis Digital Twin”, JOKI, vol. 15, no. 1, hlm. 63-72, Mei 2023.

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