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The data usage surge drives greater data center demand, amplifying global CO 2 emissions. Mitigating climate change necessitates reducing data center CO 2 emissions. Reusing waste heat from data centers offers a potential energy efficiency boost and environmental impact reduction. This study utilizes liquid cooling technology to raise waste heat temperature for building space heating and introduces the concept of 'data furnaces,' where data centers directly supply waste heat to heat buildings on-site, reducing district heating consumption and lowering CO 2 emissions. Efficiently designing a heat recovery heat exchanger system that accounts for both heat rejection and cooling sides of a liquid cooling system is crucial for achieving complete heat recovery without using heat pump, a commonly overlooked aspect in existing literature. To address this issue, we propose two heat exchanger schemes: connecting the building space heating network to the secondary side (Scheme 1) and the primary side (Scheme 2) of the cooling distribution unit. Implementing these innovations leads to the elimination of dependence on a heat pump, substantially cutting energy and CO 2 emissions. Using TRNSYS software, we develop, model, and compare waste heat recovery schemes to curb district heating consumption and CO 2 emissions. To demonstrate broad implications of the proposed approaches for energy efficiency and sustainability in the data centers and building space heating networks, a showcase study examines constant 25 kW waste heat from a direct-to-chip liquid-cooled rack in an office building with 285.7 MWh annual space heating demand. A novel waste heat recovery rate relationship graph is created to assist system design, uncovering an unexpected result in Scheme 2: waste heat recovery decreases as outdoor temperature falls. In contrast, Scheme 1 maintains a stable waste heat recovery rate around 25 kW, regardless of outdoor temperature fluctuations. As a result, Scheme 1 reuses 155.2 MWh of waste heat annually compared to 138 MWh for Scheme 2. Schemes 1 and 2 yield annual electricity savings of 2290.5 kWh and 905.2 kWh, respectively, for the cooling system. Both schemes achieve profitability within a year through a 25-year life cycle analysis (LCC) and substantially reduce CO 2 emissions, with Scheme 1 saving 291,996 kgCO 2 and Scheme 2 saving 258,192 kgCO 2. The study addresses critical gaps in existing literature by emphasizes LCC. The proposed heat exchanger designs represent pioneering solutions for optimizing waste heat recovery, particularly in challenging climates. New findings offer substantial benefits to both liquid-cooled and air-cooled facilities, making significant contributions to achieve carbon neutrality in data center operations. • Non-heat pump data center waste heat recovery for space heating is studied. • Two schemes, recovering from both sides of cooling distribution unit, are compared. • The two schemes achieve payback in under a year due to the elimination of heat pump. • Waste heat recovery on the secondary side outperforms that on the primary side. • Novel relationship graphs facilitate data center waste heat recovery system design. [ABSTRACT FROM AUTHOR]

To better make use of the waste heat in distributed data centers, a new design of integrated waste heat recovery system that can meet different needs including heating for users and data center cooling is introduced. The system can switch among different operation modes including waste heat recovery mode, natural cooling mode, composite cooling mode and refrigeration mode based on the ambient temperature. The integrated waste heat recovery system is experimented in the enthalpy-difference laboratory, and the experimental results show well consistency compared with the modeling results. The operation strategies to switch among different modes are determined based on the experimental and modeling results. The paper introduced PUE (Power Usage Effectiveness) and ERE (Energy Reuse effectiveness) to comprehensively evaluate the cooling and energy reutilization effectiveness of the system. According to the evaluation result, the integrated waste heat recovery system has well performed energy effectiveness, environmental and economic effect. The ERE values of using the integrated waste heat recovery system in Chinese typical climate cities including Harbin, Beijing, Xi'an, Shanghai and Guangzhou are 0.87, 1.02, 1.04, 1.17 and 1.29 respectively. Using this system at 96 kW distributed data center instead of CRAC (computer room air conditioning) system can save 152.7 MWh electricity, 56.4 tons of standard coal, and 244.7 tons of CO 2 emission in Beijing annually. The payback periods of this new system in different climate regions in China are all within 3 years. • An integrated data center cooling and waste heat recovery system is proposed. • Operation performance of the system is verified by experiment and modeling. • Energy Reuse Factor in Beijing is 1.02, and payback period is within 3 years. [ABSTRACT FROM AUTHOR]

Recently, waste heat recovery has enabled data centers to serve as energy prosumers with flexible features that play essential roles in the coordination operation of integrated electricity–heat systems (IEHSs). The energy hub, as a critical component of IEHSs, provides a promising opportunity to improve energy efficiency. In this paper, the decentralized coordination optimization for IEHSs with data centers is explored to protect the confidential information of different entities. First, a novel data center based energy hub (DCEH) model is developed, where energy conversion, consumption and storage present high flexibility. Especially, in addition to heat recovery, several other controllable operational characteristics of a single data center are considered, involving servers, workloads and indoor temperature. Then, the coordination optimization model of IEHSs with DCEH (IEHSs-DCEH) is constructed by incorporating energy consumption cost and carbon emission, where the energy networks of IEHSs are considered. Moreover, a learning-aided relaxed alternating direction method of multipliers (LR-ADMM) algorithm is proposed to solve the dispatching model of IEHSs-DCEH considering communication packet loss. The proposed LR-ADMM algorithm embeds a momentum extrapolation based prediction technique, which can obtain the predicted value of missing boundary information without adding computational burden, even in continuous packet losses. Simulation results demonstrate that the developed coordination dispatching model can achieve higher economic and environmental benefits than the reference one that ignores data centers' flexibility. Additionally, the proposed LR-ADMM algorithm with proper prediction factors exhibits a faster convergence rate and robustness hedging against packet losses compared to the ADMM and relaxed ADMM approaches. • A highly flexible data center based energy hub model is developed. • Impacts of the flexibility in the data center based energy hub are investigated. • The coordination of integrated energy systems with data centers is optimized. • A learning-aided decentralized algorithm is proposed hedging against packet loss. [ABSTRACT FROM AUTHOR]

This paper proposed an optimal planning method for regional integrated electricity–heat systems with data centers (DC-RIEHS) considering wind power uncertainty to reduce economic costs and improve system flexibility. First, a novel data center model is developed, where various flexible operating characteristics of the data center are modeled in detail, including thermal inertia of indoor air, rescheduling of delay-tolerant workloads, dynamic voltage frequency scaling technique of servers and heat recovery. The heat recovery system is specially built based on the electric cooling system of the studied data center and heat pump, which connects electric power systems and district heating systems. On this basis, a three-stage distributionally robust chance-constrained (DRCC) planning model of DC-RIEHS is proposed. It is converted into a tractable single-stage mixed-integer conic model by applying affine decision rules to hedge against wind power uncertainty. The proposed planning method determines the optimal capacities of energy equipment and the scheduling decisions of representative days considering wind power uncertainty. Simulation results demonstrate that the flexible resources in a data center can significantly reduce system costs and actively participate in coping with wind power uncertainty. Compared with the chance-constrained optimization method under Gaussian distribution, the proposed DRCC method exhibits better out-of-sample performance in terms of violation probability and system operation results under the wind uncertainty with spatial–temporal correlation. • A data center model is presented by considering various flexible characteristics. • The critical equipment is planned for integrated energy systems with data centers. • Distributionally robust optimization is used to deal with wind power uncertainty. • Impacts of the flexible resources in the data center are investigated. [ABSTRACT FROM AUTHOR]

• A single-phase immersion cooling system with LHTES devices is proposed. • An innovative LHTES device with palmate leaf-shaped fins is designed by bionic. • Heat charge and discharge durations reduce by 21.0% and 38.2%, respectively. • Performance of biomimetic LHTES devices is less influenced by inclination angles. • Flow rate of 20 L/min and large heat-transfer temperature difference are suggested. Improving the power usage effectiveness of data centers has become a significant challenge for carbon peaking and carbon neutrality. To address this, here we propose a single-phase immersion cooling system with latent heat thermal energy storage (LHTES) devices to recover waste heat. Furthermore, an innovative LHTES device with palmate leaf-shaped fins is designed by bionic techniques. The phase change behavior and thermal transport patterns of biomimetic and traditional LHTES devices are investigated, and the effects of the arrangement and working conditions are revealed. Additionally, the proposed solution's application prospect and economy are presented. The results indicate that the performance of palmate leaf-shaped finned LHTES devices is significantly enhanced compared to traditional ones, whose charge and discharge durations reduce by 21.0 % and 38.2 %, respectively. Moreover, the natural convection development enhances the melting performance, but its effect on solidification processes is insignificant. Considering the trade-off between power consumption and LHTES efficiency, a horizontal biomimetic LHTES device with a flow rate of 20 L/min and a large heat-transfer temperature difference is suggested in practical engineering. Notably, the maximum reduction in annual power consumption for using biomimetic LHTES devices is 2397.4 kW·h, and the minimum payback period is only 2.0 years. [ABSTRACT FROM AUTHOR]

• Discuss data centers from perspective of energy prosumers in district energy system. • Review renewable energy usage in data centers and the related advanced controls. • Review data center's waste heat recovery and reuse for district heating. • Review existing green data centers and related economic/environmental analysis. • Identify future research directions for improving data center's overall performance. As large energy prosumers in district energy systems, on the one hand, data centers consume a large amount of electricity to ensure the Information Technologies (IT) facilities, ancillary power supply and cooling systems work properly; on the other hand, data centers produce a large quantity of waste heat due to the high heat dissipation rates of the IT facilities. To date, a systematic review of data centers from the perspective of energy prosumers, which considers both integration of the upstream green energy supply and downstream waste heat reuse, is still lacking. As a result, the potentials for improving data centers' performances are limited due to a lack of global optimization of the upstream renewable energy integration and downstream waste heat utilization. This study is intended to fill in this gap and provides such a review. In this regard, the advancements in different cooling techniques, integration of renewable energy and advanced controls, waste heat utilization and connections for district heating, real projects, performance metrics and economic, energy and environmental analyses are reviewed. Based on the enormous amount of research on data centers in district energy systems, it has been found that: (1) global controls, which can manage the upstream renewable production, data centers' operation and waste heat generation and downstream waste heat utilization are still lacking; (2) regional climate studies represent an effective way to find the optimal integration of renewable energy and waste heat recovery technologies for improving the data centers' energy efficiency; (3) the development of global energy metrics will help to appropriately quantify the data center performances. [ABSTRACT FROM AUTHOR]