Optimal Sizing of Energy Station in the Multienergy System Integrated With Data Center

This article proposes a novel optimal sizing method for the energy station in the multienergy system (MES) integrated with data center. First, an overall framework of the energy station, data center, and multienergy loads is constructed to describe the interconnection of energy system and information system. Then, the dynamic voltage frequency scaling (DVFS) technique, the thermal inertia, and the deep coupling relationships of the electricity load, waste heat, cooling load, and workload in the data center are respectively modeled. On this basis, the optimal sizing model of the energy station is established, in which the data center can participate in the integrated demand response by the DVFS technique and thermal inertia. The capacity of energy station and the scheduling schemes of energy devices and servers are optimized simultaneously to coordinate the energy flow and information flow. Based on the quasi-steady-state assumption of thermal balance, the model is simplified to a mixed-integer quadratic program problem, and it is solved by Gurobi. Case studies based on a real-world test system in China illustrate that the integration of data center can be utilized to reduce the total cost of energy station planning in MES.

Automated summary

This article presents a novel optimal sizing method for the energy station in the multienergy system integrated with a data center. By modeling the dynamic voltage frequency scaling technique and the thermal inertia in the data center, the capacity of the energy station and the scheduling schemes of energy devices and servers are optimized to coordinate energy and information flow, leading to a reduction in the total cost of energy station planning in the MES.