In light of the rapid growth of data centers around the world and their huge energy consumption, several researchers have focused on the task scheduling and resource allocation problem in order to minimize the energy consumed by the data center. Other initiatives focus on the implementation of green energy sources in order to minimize the consumption of fossil fuels and their emission of CO\(_{2}\). As part of the ANR DATAZERO project (Pierson et al. in IEEE Access 7, 2019. https://doi.org/10.1109/ACCESS.2019.2930368), several research teams have engaged in efforts at defining the main concepts of a full green data center, powered only by renewable energy. Achieving this goal necessitates a focus on the efficient management of an autonomous hybrid power system consisting of solar panels, wind turbines, batteries, and fuel cell systems. The purpose of this work is not to show that a stand-alone data center is economically viable, but rather is feasible. This paper proposes a set of models based on mixed integer linear programs capable of managing the energy commitment to address data center power demand. The approach takes the season and weather forecasts into account at the time of optimization.

鉴于全球数据中心的快速增长及其巨大的能源消耗，一些研究人员将注意力集中在任务调度和资源分配问题上，以尽量减少数据中心的能源消耗。其他举措侧重于实施绿色能源，以最大程度地减少化石燃料的消耗及其二氧化碳排放\(_{2}\). 作为 ANR DATAZERO 项目（Pierson et al. in IEEE Access 7, 2019. https://doi.org/10.1109/ACCESS.2019.2930368）的一部分，几个研究团队致力于定义全绿色的主要概念数据中心，仅由可再生能源供电。实现这一目标需要重点关注由太阳能电池板、风力涡轮机、电池和燃料电池系统组成的自主混合动力系统的高效管理。这项工作的目的不是要表明独立数据中心在经济上是可行的，而是可行的。本文提出了一组基于混合整数线性程序的模型，这些模型能够管理能源承诺以解决数据中心电力需求。该方法在优化时考虑了季节和天气预报。