Towards Energy Efficient Cloud: A Green and Intelligent Migration of Traditional Energy Sources

Syed Muhammad Mohsin (), Tahir Maqsood and Sajjad Ahmad Madani
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Syed Muhammad Mohsin: Department of Computer Science, COMSATS University Islamabad, Islamabad 45550, Pakistan
Tahir Maqsood: Department of Computer Science, COMSATS University Islamabad, Lahore 55150, Pakistan
Sajjad Ahmad Madani: Department of Computer Science, COMSATS University Islamabad, Islamabad 45550, Pakistan

Energies, 2024, vol. 17, issue 11, 1-29

Abstract: Geographically distributed cloud data centers (DCs) consume enormous amounts of energy to meet the ever-increasing processing and storage demands of users. The brown energy generated using fossil fuels is expensive and significantly contributes to global warming. Considering the environmental impact caused by the high carbon emissions and relatively high energy cost of brown energy, we propose the integration of renewable energy sources (RES), especially solar and wind energy, with brown energy to power cloud data centers. In our earlier study, we addressed the intermittency of renewable energy sources, where we replaced the random initialization of artificial neural network (ANN) edge weights with the harmony search algorithm (HSA)-optimized assignment of weights. This study incorporated reliably forecast solar and wind energy into the input parameters of our proposed green energy manager (GEM), for cost minimization, carbon emission minimization, and better energy management of cloud DCs, to make our current study more reliable and trustworthy. Four power sources, on-site solar energy and wind energy, off-site solar energy and wind energy, energy stored in energy storage devices, and brown energy, were considered in this study and simulations were carried out for three different cases. The simulation results showed that case 1 (all brown) was 58% more expensive and caused 71% higher carbon emissions than case 2.1 (cost minimization). Case 1 (all brown) was 39% more expensive and had 80% higher carbon emissions than case 2.2 (carbon emission minimization). The simulation results justify the necessity and importance of the GEM, and finally the results proved that our proposed GEM is less expensive and more environmentally friendly.

Keywords: brown energy; renewable energy; cost optimization; carbon emission minimization; green energy manager (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2024
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