Towards Energy Efficiency and Power Trading Exploiting Renewable Energy in Cloud Data Centers

S. Aslam, S. Aslam, H. Herodotou, Syed Muhammad Mohsin, Khursheed Aurangzeb
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引用次数: 8

Abstract

This study investigates the energy cost and carbon emission reduction problem in geographically distributed cloud data centers (DCs), where each DC is connected with its own renewable energy resources (RERs) for green energy generation. We consider four cloud DCs that are operated by a single cloud service provider. They consume energy from both RERs and from the commercial grid to meet the demand of cloud users. For energy pricing, we consider four different energy markets that offer varying energy prices per hour. Additionally, our proposed strategy enables DCs to sell excess electricity to the commercial grid in peak-price hours and purchase in low-cost hours according to power trading. This work also exploits energy storage devices (ESDs) to store energy for future use. We utilize real-time data requests, weather data, and pricing data for performing simulations and results affirm the effectiveness and productiveness of our proposed method to mitigate the energy cost and carbon emission of cloud DCs.
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利用云数据中心的可再生能源实现能源效率和电力交易
本研究探讨了地理分布的云数据中心(DC)的能源成本和碳减排问题,其中每个数据中心都与自己的可再生能源(rer)相连,用于绿色能源发电。我们考虑由单个云服务提供商操作的四个云数据中心。为了满足云用户的需求,它们同时消耗来自可再生能源和商业电网的能源。对于能源定价,我们考虑四种不同的能源市场,它们每小时提供不同的能源价格。此外,我们提出的策略使数据中心能够根据电力交易在高峰时段将多余的电力出售给商业电网,并在低成本时段购买。这项工作还利用了能量存储设备(ESDs)来存储能量以供将来使用。我们利用实时数据请求、天气数据和定价数据进行模拟,结果证实了我们提出的方法的有效性和生产力,以降低云数据中心的能源成本和碳排放。
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