journal article·2025-08-01Open access

Research on data center load simulation and optimization of integrated energy system

Shijie Liang

AIP Advances· Volume 15· Issue 8

Abstract

Adopting an integrated energy system (IES) to power data centers can enhance the system’s economic efficiency and promote low-carbon and high-efficiency operations. Existing research primarily focuses on analyzing the energy efficiency, economic viability, and environmental characteristics of data center integrated energy systems, as well as exploring the feasibility of various energy supply methods. However, there remains a scarcity of literature that incorporates optimized operational strategies into system optimization and conducts detailed comparative analyses. Based on this, this paper constructs a model of a medium-sized data center; its cooling, heating, and electrical loads are simulated throughout the year. The IES, consisting of a photovoltaic power generation system, gas turbine, waste heat boiler, electric chiller, and absorption chiller, is established. By comparing the operating strategies of Following Thermal Load (FTL) and Following Electric Load (FEL), an optimization analysis is then carried out to determine the integrated energy system configuration that minimizes the data center’s annual operating costs. The main contributions of this work include (1) load simulation of the entire data center building to analyze its heating, cooling, and electrical load characteristics; (2) comparison of the operational cost optimization of FTL and FEL strategies using particle swarm optimization algorithms; and (3) based on the optimization results, analysis of the output proportions of various equipment under different strategies, revealing that the FTL strategy reduces operating costs by 20%, 6%, and 7.2% in winter, summer, and the transition season, respectively, with winter days exhibiting the lowest costs, transitional seasons showing moderate costs, and summer days the highest. This strategy can effectively reduce the costs and instability of the IES and provide a reference for the design of energy supply systems for data centers.
Source: crossref · Quality: baseline

Research context

OpenAlex topics: Heat Transfer and Optimization · Cloud Computing and Resource Management · Green IT and Sustainability

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

International Education Institute, North China Electric Power University , Baoding 071003,

References (14)

Show source-provided references
1. On global electricity usage of communication technology: Trends to 203010.3390/challe6010117 ↗
2. Integrated optimization of configurations and operations of integrated energy system for data center
3. Energy, environmental, and economic evaluation of a CCHP system for a data center based on operational data10.1016/j.enbuild.2013.08.021 ↗
4. Economic feasibility study of a fuel cell-based combined cooling, heating and power system for a data centre10.1016/j.enbuild.2015.11.012 ↗
5. Strategy analysis of natural gas trigeneration system in the application of new data centers
6. Evolution, driving mechanism, and pathway of China’s energy transition10.19744/j.cnki.11-1235/f.2021.0109 ↗
7. Application of multi-energy complementary distributed energy system in data center10.13608/j.cnki.1000-4416.2021.09.005 ↗
8. Integrated energy systems of data centers and smart grids: State-of-the-art and future opportunities10.1016/j.apenergy.2021.117474 ↗
9. Low-carbon planning of data center integrated energy system under risk avoidance
10. Research on optimal configuration for integrated energy system with liquid air energy storage combined heat and power supply10.19799/j.cnki.2095-4239.2024.0045 ↗
11. Energy, exergy and exergo economic optimization of a proposed CCHP configuration under two different operating scenarios in a data center: Case study10.1016/j.jclepro.2022.130971 ↗
12. Optimal cost management of the CCHP based data center with district heating and district cooling integration in the presence of different energy tariffs10.1016/j.enconman.2022.115211 ↗
13. Optimal scheduling of micro grid with CCHP systems based on improved particle swarm optimization algorithm
14. Multi-time scale coordinated optimal control method for ADN considering source load prediction error