Coordinated optimal scheduling of integrated energy system for data center based on computing load shifting

High-efficiency uninterruptable power supplies and sustainable energy systems are essential to realize data centers more sustainable and environmentally friendly. Considering the coupling between computing tasks and power consumption, this paper proposes a coordinated optimization model of operational scheduling of integrated energy system (IES) for data center according to computing load transfer. An IES consisting of solar photovoltaic arrays, gas engine, and organic Rankine cycle is proposed and optimized to obtain the optimum component capacities. Then, the computing tasks of servers with task shifting are modeled to characterize the arrival time, execution time, and deadline of different tasks. The operation scheduling optimization model of components in the IES with the computing task transfer is proposed to minimize the operating costs of data center and maximize the user satisfaction level of computing tasks. The impacts of objective weights on the dispatch strategies of the IES and computing tasks are discussed. The optimization results in a case study demonstrate that the data center can effectively realize the transfer of electricity and cooling loads by transferring computing tasks to improve the IES performances. The optimum dispatch strategies with task transfer saves operational cost and fuel consumption by 2.76% and 2.56%, respectively, and the carbon dioxide emission is reduced by 6.31% in non-heating season. Their benefits in heating season are 3.47%, 4.11%, and 2.17%, respectively.