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Co-scheduling of datacenter and HVAC loads in mixed-use buildings

机译:混合使用建筑物中数据中心和HVAC负荷的协同调度

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The majority of datacenters are within mixed-use facilities, where they often share some common infrastructures and energy supplies with other operations (e.g., non-IT offices and labs). In such mixed-use buildings, two major energy loads are datacenter IT equipment and HVAC (heating, ventilating, and air conditioning) system. The HVAC demand comes from both datacenter rooms and other non-IT rooms. To effectively lower peak demand and reduce energy cost for mixed-use buildings, it is important to leverage the scheduling flexibility from both the HVAC system and the delay-tolerant datacenter workload in a collaborative fashion. In this work, we model the major physical and cyber components of mixed-use buildings, and propose a model predictive control (MPC) formulation to co-schedule datacenter and HVAC loads, with consideration of solar energy and battery storage. The MPC formulation minimizes building energy cost while satisfying various requirements on room temperature, ventilation, and datacenter workload deadlines. Compared with separate scheduling strategy, our approach significantly reduces peak demand and overall energy cost, and provides better leverage of renewable energy supply. Furthermore, we demonstrate that our formulation is also effective in reducing carbon footprint, and balancing its trade-off with energy cost.
机译:大多数数据中心都位于混合使用设施中,它们经常与其他业务(例如,非IT部门和实验室)共享一些通用的基础架构和能源供应。在这样的混合用途建筑中,两个主要的能源负荷是数据中心IT设备和HVAC(供暖,通风和空调)系统。 HVAC需求来自数据中心机房和其他非IT机房。为了有效降低高峰期需求并降低混合用途建筑物的能源成本,重要的是要以协作的方式利用HVAC系统和耐延迟数据中心工作负载的调度灵活性。在这项工作中,我们对混合用途建筑物的主要物理和网络组成部分进行建模,并提出了模型预测控制(MPC)公式来共同调度数据中心和HVAC负荷,同时考虑了太阳能和电池存储。 MPC的配方可最大程度地降低建筑物的能源成本,同时满足对室温,通风和数据中心工作负载期限的各种要求。与单独的调度策略相比,我们的方法显着降低了峰值需求和总体能源成本,并提供了更好的可再生能源供应杠杆。此外,我们证明了我们的配方还可以有效减少碳足迹,并在权衡与能源成本之间取得平衡。

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