To meet the low-carbon and economic demands of data centers

an energy scheduling optimization model for data centers with the objectives of minimizing carbon emissions and comprehensive energy costs is established. An improved non-dominated sorting genetic algorithm-II（NSGA-II）with enhanced speed and elite mechanism is proposed to solve the model. Firstly

the optimization scheduling framework for data center comprehensive energy systems is introduced

considering the load response characteristics of data centers and equipment energy consumption models

and an energy scheduling optimization model for data centers with economic and low-carbon objectives is established. Secondly

addressing the issue of uneven distribution of Pareto solution sets and poor diversity in traditional NSGA-II

an enhanced NSGA-II algorithm is proposed. It adopts dynamic distance comparison and elite retention selection of individuals to ensure both excellent solutions and improved diversity. Finally

through a case study of energy scheduling in a particular data center

the effectiveness of the model and method in reducing data center carbon emissions and comprehensive energy system costs is verified.