QoS‐Based Bi‐Level Demand Response for Data Center to Facilitate Renewable Energy Integration

Author:

Li Bin1,Cao Wangzhang1,Tang Tianyue1,Qi Bing1,Zhao Jianli2,Liu Chuan3

Affiliation:

1. School of Electrical and Electronic Engineering North China Electric Power University Beijing China

2. State Grid Shanghai Municipal Electric Power Company Shanghai China

3. State Grid Electric Power Research Institute Nanjing Branch Jiangsu China

Abstract

Scheduling workload is a demand response strategy for data centers to reshape electricity usage, which provides an opportunity for them to utilize renewable energy. Enhancing the flexibility of workload scheduling would promote the data center to integrate renewable energy. Considering that the improvement of flexibility in workload scheduling is tightly related to the Quality of Service (QoS) required by IT consumers (ITCs), it becomes desirable for the data center to collaborate with them to further facilitate renewable energy integration in demand response programs. This paper proposes a QoS‐based bi‐level demand response model for the data center, where game theory is adopted to resolve the conflict of interest in the collaboration between the data center and ITCs. At the upper level, the data center is a leader who provides differential monetary incentives to ITCs while dispatching workload to integrate renewable energy. At the lower level, ITCs act as followers who adjust the workload's QoS to enhance the flexibility of workload scheduling. Simulation results show that the proposed model can decrease the operating cost of the data center while increasing the utilization of renewable energy. © 2024 Institute of Electrical Engineer of Japan and Wiley Periodicals LLC.

Publisher

Wiley

Reference35 articles.

1. DanilakR.Why energy is a big and rapidly growing problem for data centers. Available:2017.https://www.forbes.com/sites/forbestechcouncil/2017/12/15/why‐energy‐is‐a‐big‐and‐rapidly‐growing‐problem‐for‐data‐centers/.

2. Optimization-based workload distribution in geographically distributed data centers: A survey

3. Sustainable Cloud Data Centers: A survey of enabling techniques and technologies

4. Carbon-Aware Energy Cost Minimization for Distributed Internet Data Centers in Smart Microgrids

5. Energy and Network Aware Workload Management for Sustainable Data Centers with Thermal Storage

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