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Data centers (DCs) are gradually becoming one of the world's largest energy consumers. Owing to their spatial-temporal transferable characteristics, DCs show great potential in demand response (DR) programs. Considering the difference in task delay sensitivity (TDS), an elaborate DR model of DCs is proposed in this work. Furthermore, to ensure the TDS requirement and relieve the data transmission pressure, TDS-based unit migration cost matrices are designed in this work. Given that most DR dispatch for DCs is conducted relying on a central dispatching center, which imposes critical requests for the reliability of the dispatching system. In this work, we establish a novel 4-level joint optimal dispatch model for the DC operator, where dispatching centers installed at each level integrate district information from bottom to top and conduct optimal task dispatch from top to bottom. Moreover, an innovative dispatch autonomy mechanism is designed to realize district autonomy in the case of dispatching center breakdowns. Finally, simulation results prove that the proposed 4-level joint optimal dispatch model has a positive effect on enhancing renewable energy accommodation and improving the economic benefits of the DC operator. More specifically, by applying the proposed 4-level joint optimal dispatch model, the DCO's total cost is decreased by 32.25% in comparison with the result of no DR participation. It also proves that our designed dispatch autonomy mechanism can achieve district autonomy under the breakdown of dispatching centers at any level. • Propose a novel 4-layer joint optimal dispatch model for data center operator • Establish an elaborate demand response model of data centers based on task delay sensitivity • Design an innovative dispatch autonomy mechanism to realize district autonomy [ABSTRACT FROM AUTHOR]

Multiple geographically dispersed data center buildings have been increasingly positioned in renewable-rich areas due to their high energy consumption. This paper proposes an optimal multi-energy portfolio for zero carbon data center buildings in the presence of proactive demand response programs. In the data center buildings, the complementarities of hydro-solar-wind hybrid renewable energy sources (RESs) are fully exploited via multi-energy conversion and storage devices, which are modeled as 100% renewable energy hubs for zero carbon multi-energy supplies. In order to exploit the hub-internal operational dispatchability and flexibility, a comprehensive energy consumption model of data center buildings is proposed to facilitate the demand response in terms of available serves, while the variable speed pumped storage (VSPS) is modeled to capture its dynamic operational characteristics. The energy‑carbon production, conversion, storage, and consumption are formulated as an energy‑carbon matrix, which are solved via a two-stage method to obtain the optimal portfolio. Case studies on southwest China data center buildings are implemented to demonstrate the effectiveness and superiority of the proposed methodology on cost-effective accommodation of RESs. Simulations results show that the system portfolio cost can be reduced by at most 17.8% with a higher operational flexibility. • A cost-effective data center building is proposed to accommodate zero carbon targets. • Hydro-solar-wind 100% renewables are formulated for multi-energy supplies. • VSPS and data center energy consumption are modeled to exploit inherent flexibility. • The energy-carbon production, conversion, storage, and consumption are optimized. [ABSTRACT FROM AUTHOR]

Electricity cost has become a critical concern of data center operations with the rapid increasing of information processing demand. Data center microgrid (DCMG) is a promising way to reduce electric energy consumption from traditional fossil fuel generators and the billing cost, by effectively utilizing local renewable energy, e.g., wind power. However, uncertainties of wind power generation and real-time workload of data center would have significant impacts on the operational efficiency of DCMG, especially when it is in the island mode. For this reason, a novel affinely adjustable policy based robust multi-objective optimization model under flexible uncertainty set is proposed in this paper, which simultaneously optimizes wind power curtailment, the operation cost, and the over-plus level of computation resource, while considering uncertainties of both the wind power and real-time workload. Through numerical simulation studies, the validity of robust multi-objective optimization model for the island operation of DCMG is verified. Besides, the effectiveness of the proposed methods, i.e., the novel affinely adjustable policy and the flexible uncertainty set, in handling uncertainties are evaluated. Compared to the conventional robust multi-objective optimization model, the proposed approach reduces the operating costs of about 10% in average while maintaining similar reliability in numerical simulations. Moreover, the complex quantitative relationship among these multiple objectives is further investigated. Simulation results indicate the minimization of wind power curtailment and over-plus level of computation resource increases about 25% of the operation cost. These quantitative relationships can well support the decision making of DCMG operation management. • A novel robust multi-objective scheduling model is proposed to study the relationship between the multi-objectives of the islanded data center microgrid. • The flexible uncertainty set and the affine adjustable policy are developed to effectively handle the uncertainty factors, i.e., less conservative Pareto optimal solutions could be obtained. • Numerical simulation studies are executed to verify the validity of robust multi-objective optimization model and the effectiveness of the developed novel affinely adjustable policy as well as the flexible uncertainty set. [ABSTRACT FROM AUTHOR]

• System design of energy-saving superconducting cables from renewable energy to a 100 MW data center. • Technical design of compact multi-layer superconducting cables with the details of materials' characteristics. • Total loss of superconducting cables decreasing down to 1.7% of the loss of conventional AC/DC cables. • Economic advantages of superconducting cables over conventional cables due to the extremely low operating costs. • Promising solution using energy-saving superconducting cables for the hyper-scale data centers due to the technical and economic benefits. With the significant increase of global data center infrastructure, how to delivery electric energy to data centers in an efficient and sustainable way needs to be carefully considered. This article presents a novel study on the energy-saving superconducting cables from the renewable energy source to a 100-MW-class data center, with the comparison using the conventional AC and DC power transmissions (9 cases in total). The design of superconducting cables and AC and DC power cables are shown with the details of materials, electrical and thermal characteristics. For all these transmission schemes, both the capital investment costs and operating costs are derived, and the economic analysis is carried out with the factors of different voltage levels, transmission distances from clean energy to the data center, and operating years. Results show the transmission schemes by superconducting cable have both the technical and economic advantages over the conventional AC and DC transmission schemes (e.g., for the 10 kV 10 km case, the total energy loss of superconducting transmission is merely 1.7% of conventional AC, and after 10 years the total cost of superconducting transmission is also cheaper), which can be a promising solution of energy transmission for the high-power data centers in the future. [ABSTRACT FROM AUTHOR]

• Cooling solution adopts heat exchanger/evaporative water chiller on air/water sides. • Thermal control is enhanced using overhead downward flow with cold aisle containment. • Effects of supply air temperature and velocity on data center performance are studied. • A good power usage efficiency of 1.38 is achieved for planned large-scale data center. This study proposes the container data center with the featured cold aisle containment (CAC) as effective thermal control strategy. In design, the overhead downward flow system is implemented with a heat exchanger arranged right above the data center on the air side and an evaporative water chiller on the water side to form the cooling approach. The cold airflows and hot exhausts of racks are separately transported by the contained cold and hot aisles to alleviate the problem of cold and hot air mixing. The measurements of air temperature and velocity of racks are used to validate the prediction accuracy of the computational fluid dynamics (CFD) model. The performance metrics in terms of the rack cooling index (RCI), return temperature index (RTI), supply heat index (SHI) are used to examine the design effectiveness of the proposed test data center. The simulations are then extended to assess the air distribution and thermal management at varied supply air temperatures and velocities for a large-scale data center to be built in the green energy technology demonstration site of the Shalun smart green energy science city. Overall, the calculated average PUE of 1.38 for the large-scale data center is notably less than the average PUE of 1.59 from the results of 2020 data center industry survey, indicating the potential savings of cooling energy and cost. This paper demonstrates a generalized approach as an easily adaptable, cost-effective solution for data centers to be deployed in tropical and subtropical areas. [ABSTRACT FROM AUTHOR]

• Review the state-of-the-art research works of integrated energy systems of data centers and smart grids. • Propose future integration scenarios for data centers and smart grids. • Analyze the challenges of implementing integrated energy systems of data centers and smart grids. Cloud computing platforms are critical cyber infrastructures in modern society. As the backbone of cloud systems, data centers act as large energy consumers in today's power grids. The integration of on-site renewable energy sources and energy storage systems further transforms data centers to be energy prosumers (producers-and-consumers). As a result, optimizing data centers' energy production and consumption, and exploiting their potential of actively engaging in the external grid's planning, operation, and control has been drawing increasing attention in the last few years. This paper conducts a comprehensive review of the state-of-the-art research efforts on integrated energy systems of data centers and smart grids. A taxonomy of such integration scenarios is provided. Consequently, this paper identifies several future application scenarios of integrating data centers and smart grids, which serves as a roadmap towards future research. This article is expected to provide a useful reference for researchers and engineers in the areas of energy systems and cloud computing. [ABSTRACT FROM AUTHOR]