相关论文: Electricity Price-Aware Scheduling of Data Center …
In response to the increasing deployment of battery storage systems for cost reduction and grid stress mitigation, this study presents the development of a new real-time Markov decision process model to efficiently schedule battery systems…
We formulate optimization problems to study how data centers might modulate their power demands for cost-effective operation taking into account three key complex features exhibited by real-world electricity pricing schemes: (i)…
Price-based demand response (DR) of heating, ventilating, and air-conditioning (HVAC) systems is a challenging task, requiring comprehensive models to represent the building thermal dynamics and game theoretic interactions among…
Manufacturing industries are among the highest energy-consuming sectors, facing increasing pressure to reduce energy costs. This paper presents an energy-aware Model Predictive Control (MPC) framework to dynamically schedule manufacturing…
Leveraging electrochemical and thermal energy storage systems has been proposed as a strategy to reduce peak power in data centers. Thermal energy storage systems, such as chilled water tanks, have gained increasing attention in data…
Thermal-aware workload distribution is a common approach in the literature for power consumption optimization in data centers. However, data centers also have other operational costs such as the cost of equipment maintenance and…
Power management in multi-server data centers~especially at scale is a vital issue of increasing importance in cloud computing paradigm. Existing studies mostly consider thresholds on the number of idle servers to switch the servers on or…
In this paper, we study a problem of controlling cooling facilities and computational equipments for energy-efficient operations of data centers. Although a plethora of approaches have been proposed in previous literatures, there is a lack…
Model predictive control (MPC) strategies allow residential water heaters to shift load in response to dynamic price signals. Crucially, the performance of such strategies is sensitive to various algorithm design choices. In this work, we…
Data centers have emerged as promising resources for demand response, particularly for emergency demand response (EDR), which saves the power grid from incurring blackouts during emergency situations. However, currently, data centers…
Thermal management in the hyper-scale cloud data centers is a critical problem. Increased host temperature creates hotspots which significantly increases cooling cost and affects reliability. Accurate prediction of host temperature is…
Cloud computing revolutionised the industry with its elastic, on-demand approach to computational resources, but has lead to a tremendous impact on the environment. Data centers constitute 1.1-1.5% of total electricity usage in the world.…
This paper develops risk-averse models to support system operators in planning and operating the electricity grid under uncertainty from renewable power generation. We incorporate financial risk hedging using conditional value at risk…
Data centers (DCs) are emerging as large, geographically distributed, controllable loads whose participation in electricity markets can significantly affect grid operation, especially when cloud platforms shift workloads across sites to…
Model predictive control (MPC) has been shown to significantly improve the energy efficiency of buildings while maintaining thermal comfort. Data-driven approaches based on neural networks have been proposed to facilitate system modelling.…
An electricity bill of a data center (DC) is determined not only by how much energy the DC consumes, but especially by how the consumed energy is spread over time during the billing cycle. More specifically, these electricity costs are…
It is estimated that data centers constitute 1.5% of global electricity usage. At the same time, to serve increasing user requirements, modern cloud providers are operating multiple geographically distributed data centers. Distributed data…
Economic model predictive control has been proposed as a means for solving the unit loading and unit allocation problem in multi-chiller cooling plants. The adjective economic stems from the use of financial cost due to electricity…
Cooling system plays a critical role in a modern data center (DC). Developing an optimal control policy for DC cooling system is a challenging task. The prevailing approaches often rely on approximating system models that are built upon the…
With the current high levels of energy consumption of data centers, reducing power consumption by even a small percentage is beneficial. We propose a framework for thermal-aware workload distribution in a data center to reduce cooling power…