Design and research of a total-auxiliary-system (TAS) for temperature and humidity control of underwater data center

ABSTRACT

Underwater data centers, with their low energy use, cost, and latency, are seen as the future of data centers. This paper designs a Total Auxiliary System (TAS) for underwater data centers, including temperature and humidity control unit, biofouling prevention, and seawater corrosion prevention. In this paper, a model for the temperature and humidity control unit was developed, and key parameters such as heat load, specific moisture extraction rate (SMER), coefficient of performance (COP), and dehumidification volume were simulated. The effectiveness of the cooling performance was verified using Computational Fluid Dynamics (CFD) simulations. The system design also includes biofouling prevention via electric pulse and seawater corrosion prevention using cathodic protection with plastic coating and applied current. Calculations and verifications show that this system reduces energy consumption and ensures the long-term stable operation of underwater data centers.

KEYWORDS:

• Underwater data centers
• total auxiliary system (TAS)
• temperature and humidity control
• biofouling prevention
• seawater corrosion prevention
• energy efficiency

Acknowledgements

The corresponding author, Guopeng Yu, acknowledges the support of Guangdong Talent Program (2021QN020467).

Disclosure statement

No potential conflict of interest was reported by the author(s).

Nomenclatures

Abbreviations	=
TAS	=	total Auxiliary System
SMER	=	specific moisture extraction rate
COP	=	coefficient of performance
CFD	=	computational Fluid Dynamics
UDC	=	underwater data center
IoT	=	Internet of Things
SOFCs	=	solid oxide fuel cells
NSGA-II	=	non-dominated Sorting Genetic Algorithm-II
RaaS	=	reservoir as a service
MaRC	=	maintenance and repair cost
IIn	=	initial investments
Symbols	=
Φ	=	heat flow rate
A	=	heat transfer area
k	=	heat transfer coefficient
$t_{\mathit{f}1}$	=	air temperature
$t_{\mathit{f}2}$	=	seawater temperature
$h_1$	=	surface heat transfer coefficient of air
$h_2$	=	surface heat transfer coefficient of seawater
$\mathit{\delta }$	=	thickness of the enclosure
$\mathit{\lambda }$	=	thermal conductivity
η	=	compressor efficiency
h	=	enthalpy
s	=	entropy
P	=	pressure
Q	=	gas content
${\mathrm{d}}_{\mathrm{a}}$	=	moisture content in the air
${\mathrm{d}}_{\mathrm{e}}$	=	moisture content of the solution
$\mathrm{NT}{\mathrm{U}}_{\mathrm{m}}$	=	the number of mass transfer units
$\mathrm{Le}$	=	Lewis number
$\mathrm{X}$	=	solution quality fraction
$\mathit{\rho }$	=	fluid density
$\vec{u}$	=	fluid velocity vector
$\mathit{p}$	=	fluid pressure
$\mathit{\mu }$	=	fluid dynamic viscosity coefficient
$G_k$	=	turbulent kinetic energy generated by the laminar velocity gradient
${\mu }_t$	=	turbulent viscous coefficient
$C_{1\mathrm{s}}$$C_{2\mathrm{s}}$$C_{\mu }$	=	empirical constants
${\sigma }_k$	=	turbulent kinetic energy
${\sigma }_s$	=	turbulent dissipation rate Trump numbers
$Z_j$	=	static payback period
$Z_D$	=	dynamic payback period
${\mathrm{\Delta }}_t$	=	difference in investment costs
${\mathrm{\Delta }}_y$	=	difference in annual operating costs
i	=	discount rate
$P_{\mathit{cooling},\mathit{j}}$	=	cooling load of the data center for month j
$T_j$	=	operating time for month $\mathit{j}$
$P_{\mathit{pump}}$	=	rated power of the pump.
$E_{\mathit{TAS}}$	=	annual operating energy consumption of TAS
$E_{\mathit{com},\mathit{TAS}}$	=	annual operating energy consumption of compressor
$E_{\mathit{pump}}$.	=	annual operating energy consumption of pump
$P_{\mathit{com},\mathit{tradiction}}$	=	reference power of traditional system
R	=	maintenance and repair cost factor

Additional information

Funding

The work was supported by the Guangdong Talent Program (No. 2021QN020467).