Configuration Optimization Model for Data-Center-Park-Integrated Energy Systems under Economic, Reliability, and Environmental Considerations

Zhiyuan Liu, Hang Yu, Rui Liu, Meng Wang and Chaoen Li
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Zhiyuan Liu: School of Mechanical and Energy Engineering, Tongji University, Siping Road No.1239, Shanghai 200092, China
Hang Yu: School of Mechanical and Energy Engineering, Tongji University, Siping Road No.1239, Shanghai 200092, China
Rui Liu: School of Mechanical and Energy Engineering, Tongji University, Siping Road No.1239, Shanghai 200092, China
Meng Wang: School of Mechanical and Energy Engineering, Tongji University, Siping Road No.1239, Shanghai 200092, China
Chaoen Li: School of Mechanical and Energy Engineering, Tongji University, Siping Road No.1239, Shanghai 200092, China

Energies, 2020, vol. 13, issue 2, 1-22

Abstract: The analysis of energy configuration in the planning of data-center-park-integrated energy systems (DCP-IESs) has become an enormous challenge, owing to multi-energy complementarity, energy cascade use, and energy security. In this study, a configuration model of DCP-IESs was established to obtain the economic and low-carbon energy uses of the data centers, based on mixed integer linear programming. In the model, carbon emissions were converted to economic indicators through carbon pricing. Then, the configuration model was modified according to the security of the proposed device switching logic, and the Markov-based reliability estimation method was used to ensure the redundant design of the configuration. Using the new energy configuration method, the DCP-IES configuration scheme could be obtained under economical, low-carbon, and high reliability conditions. A data center park in Shanghai was selected as a case study, and the results are as follows: it will only take 2.88 years for the economics of DCP-IES to reach those of traditional data center energy systems. Additionally, the use of configuration model in DCP-IES would result in a reduction in annual carbon emissions of 39,323 tons, with a power usage effectiveness of 1.388, whereas an increase in reliability results in an increasingly faster increase in the initial investment cost.

Keywords: integrated energy system; configuration model; cost and low-carbon; device pre-start; reliability analysis; redundant design (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: 2020
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (3)

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