Optimizing data center energy consumption via energy complementarity scheduling

Considering the degree of flexible energy supply and demand matching, four types of energy sources were combined and a dynamic multi-energy combination optimization scheduling model was established for data centers to realize the optimal scheduling of multiple energy sources to meet the minimum overall energy consumption of data centers. Model construction and simulation analysis were used to conduct the research. To maximize the use of wind power and photovoltaic renewable energy, a multi-objective optimization scheduling model was constructed with the objectives of maximum flexibility of supply and demand matching in a single day, minimum penalty for predicted photovoltaic power consumption, minimum average service time of data centers, and minimum overall energy consumption of data centers. The NSGA-III framework was used to solve the constructed model. The results showed that even in areas rich in renewable energy, because of the limited power of renewable energy generation, the purchase of electric energy and natural gas as the main energy source remained necessary to ensure the stable operation of data centers. Data centers can use the complementarity of photovoltaic and wind power generation times to achieve basic complementarity of power generation. In terms of cooling energy consumption, natural gas waste heat-driven absorption refrigerator output accounted for a significant proportion, approximately twice that of the electric refrigerator and could effectively reduce the energy consumption of electric refrigeration. The simulation results of energy scheduling model show that it is necessary to increase the proportion of natural gas and green energy in data center energy supply, maximize the use of renewable energy such as wind power and photovoltaic power generation, give full play to the characteristics of wind power and photovoltaic power generation time complementarity, and build a green energy complementary data center energy supply mode.

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Publication Details

Journal
Energy Reports
Published
2024-12-01
DOI
https://doi.org/10.1016/j.egyr.2024.11.032
Citations
13
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
10.13
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article

Optimizing data center energy consumption via energy complementarity scheduling

Guisheng Hou, Lei Yang, Xuehui Liu
13 citations
Energy Reports
Cloud Computing and Resource Management
10.13
article

Optimizing data center energy consumption via energy complementarity scheduling

Guisheng Hou, Lei Yang, Xuehui Liu
article en
13 citations

Abstract

Considering the degree of flexible energy supply and demand matching, four types of energy sources were combined and a dynamic multi-energy combination optimization scheduling model was established for data centers to realize the optimal scheduling of multiple energy sources to meet the minimum overall energy consumption of data centers. Model construction and simulation analysis were used to conduct the research. To maximize the use of wind power and photovoltaic renewable energy, a multi-objective optimization scheduling model was constructed with the objectives of maximum flexibility of supply and demand matching in a single day, minimum penalty for predicted photovoltaic power consumption, minimum average service time of data centers, and minimum overall energy consumption of data centers. The NSGA-III framework was used to solve the constructed model. The results showed that even in areas rich in renewable energy, because of the limited power of renewable energy generation, the purchase of electric energy and natural gas as the main energy source remained necessary to ensure the stable operation of data centers. Data centers can use the complementarity of photovoltaic and wind power generation times to achieve basic complementarity of power generation. In terms of cooling energy consumption, natural gas waste heat-driven absorption refrigerator output accounted for a significant proportion, approximately twice that of the electric refrigerator and could effectively reduce the energy consumption of electric refrigeration. The simulation results of energy scheduling model show that it is necessary to increase the proportion of natural gas and green energy in data center energy supply, maximize the use of renewable energy such as wind power and photovoltaic power generation, give full play to the characteristics of wind power and photovoltaic power generation time complementarity, and build a green energy complementary data center energy supply mode.

Energy ReportsVol. 12
Shandong University of Science and Technology (CN)
Affordable and clean energy
Openalex Percentile: Top 2%
Cloud Computing and Resource Management
10.13
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Optimizing data center energy consumption via energy complementarity scheduling — Guisheng Hou, Lei Yang, et al. · Energy Reports (2024) | TGRS Research Map | TGRS