Optimal Planning of Internet Data Centers Decarbonized by Hydrogen-Water-Based Energy Systems

Green and sustainable development of Internet data centers (IDCs) has attracted more attention in both academia and industry. Full utilization of renewable energy sources is widely known as the most effective way to supply electrical and thermal energy while reducing carbon emission. However, the integration of renewable energy into IDCs is still challenging due to the mismatch between uncertain renewable supply and time-varying demand requirements, and high requirement of operation reliability against IDC failures. Therefore, in this paper a hydrogen-water-based energy (HWBE) system is developed and its integrated planning-and-operation problem is formulated as a mixed-integer linear programming problem to determine the optimal capacity of energy facilities in the HWBE system with considering IDC operation reliability. A hybrid physics-based and data-driven method is developed to accurately capture the electrical and thermal energy consumption characteristics and their coupling which are the basis for the optimal planning of the HWBE system. Furthermore, a Benders decomposition-based reliability improvement algorithm is developed to enhance the operation reliability, which decomposes the problem into the planning problem with normal operation as the master problem and the operation problem with IDC failure as the subproblem. The reliability can be enhanced using the solution obtained by the master problem with the feasibility cut obtained from the subproblem. Numerical results show that the developed HWBE system is energy-efficient with low carbon emission, since the power usage efficiency of IDCs could be as low as 1.09 and the carbon emission could be reduced by 74.9% as compared by the electricity-driven IDC energy system.
Note to Practitioners
—This paper focuses on the integrated planning-and-operation optimization of an HWBE system for the application in IDCs. We improve the energy consumption model of IDCs based on a hybrid physics-based and data-driven method, which can describe the interaction between the dynamic thermal process and electricity consumption of IDCs. In this way, both the high accuracy of the physics-based model and the lower computational effort of the data-driven method could be simultaneously achieved in the energy consumption model. Furthermore, in practice, the optimal planning problem of IDCs is necessary to take into account the operation reliability against data center failures, since the capital expenditure of the backup energy devices is generally significant. This means that a trade-off between the solution accuracy of the planning problem and the computational complexity caused by the operation problem should be considered. Therefore, we develop a Benders decomposition-based reliability improvement algorithm to address the trade-off mentioned above. This technique can integrate the feasibility cut obtained from the operation problem with IDC failure into the planning problem, in order to improve the operation reliability against the supply-demand mismatching and IDC failures while reducing the capital cost, as compared to the system designed by the conventional redundancy standard. Numerical results show the effectiveness of the developed method which can make full use of renewable energy sources and support the green and sustainable development of IDCs.