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March 6, 2026Journal of Cleaner Production3 citationsOpen Access

Synergistic optimization of computing-power-cooling-heat multi-energy flow: Integrating flexible data centers and district heating networks

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CFChao FuKZKai ZhangCDChuanzi Deng

Key Points

  • The aim is to develop a framework for optimizing energy flows within data centers and district heating networks to enhance efficiency and sustainability.
  • Developed a holistic framework for coordinating energy flows in computing and heating systems.
  • Established a closed-loop energy chain for balancing electricity, cold, and heat dynamically.
  • Implemented a double-layer optimization method for design and operation.
  • Conducted a case study comparing three operational configurations to validate the approach.
  • Achieved a 19% reduction in total costs versus the baseline.
  • Realized a 32% decrease in carbon emission costs compared to the inflexible setup.
  • Demonstrated significant renewable energy integration and operational flexibility.

Abstract

Mining flexible and reliable resources on both energy consumption side and during transmission process to match the fluctuations of renewable energy sources can reduce system capacity requirements and enhance operational performance. However, a major challenge lies in the seamless coordination and real-time management of diverse energy flows. This study presents a holistic framework that coordinates computing-power-cold-heat multi-energy flows across data centers, integrated energy systems, and district heating networks, enabling chained optimization and system-wide synergistic operation. This synergy is achieved by establishing a closed-loop energy flow where the flexibility of data center computing loads and the virtual thermal storage of the heating network are coordinated to balance multi-energy supply and demand dynamically. By leveraging them, the approach establishes a closed-loop energy chain that not only enhances renewable energy integration and waste heat recovery but also enables real-time balancing of electricity, cold, and heat demands. A double-layer optimization method is proposed to co-optimize system design and operation of the chained system. The outer layer configures components’ capacities, while the inner layer schedules computing workloads, temperature regulation of networks, and multi-energy flows, resolving configuration-operation interdependencies. A case study validates the proposed methods through comparing three cases. The simulation results demonstrate that the scheme with the flexibilities of data center and heating networks achieves a 19% reduction in total cost and a 32% decrease in carbon emission costs compared to the baseline without workload shifting and heat storage in heating networks, significantly enhancing renewable integration and operational flexibility. • The coupled system of data center, integrated energy system and heating networks is optimized. • Leveraging data center workload shifting with heating network virtual thermal storage flexibility. • Closed-loop energy chain integrates computing-power-cold-heat flows. • 19% total cost & 32% carbon cost reduction vs. inflexible baseline. • Virtual storage of heating network shifts 19.26 MWh daily heat, cutting curtailment 71%.

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Cite This Study

Fu et al. (2026) studied this question.

synapsesocial.com/papers/69aa6ee2531e4c4a9ff590a9https://doi.org/10.1016/j.jclepro.2026.147782
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