能源互联网下基于储能调度及多源供能的数据中心能效优化

发布时间：2018-03-09 04:33

本文选题：储能调度　切入点：多源供能　出处：《计算机研究与发展》2017年04期 　论文类型：期刊论文

【摘要】：近年来,数据中心能效优化问题得到业界的普遍关注.同时,能源互联网的发展为数据中心能效优化问题提供了新的研究思路.能源互联网中的用户,尤其是大型的工业用户,通常具备一定的储能能力和一定的智能化能源管理能力.随着清洁能源的大规模部署以及售电公司的快速发展,数据中心等大型能耗用户也随之获得购电的选择权,可以根据电价、清洁程度等因素,从不同的能源供应商购买能源,从而降低能源成本,提高能效.研究表明在污染指数及实时电价的调节下,用户更趋向于在用电低谷期买入更多廉价且清洁的能源.因此,一方面综合考虑污染指数函数与实时电价,构建多源购电成本模型;另一方面综合考虑储能的操作成本及潜在收益成本,构建储能充放电成本模型,简称储能成本模型.以此为基础,建立了有储能系统下的数据中心多源能源选择模型,并与无储能时序调度策略时的系统性能做了对比.仿真结果表明:提出的模型可以通过对储能时序及多源能源选择的综合优化,一定程度上降低数据中心的日能源成本,同时提高清洁能源利用率.
[Abstract]:In recent years, the energy efficiency optimization of data centers has received widespread attention. At the same time, the development of energy Internet has provided a new research idea for energy efficiency optimization in data centers. With the large-scale deployment of clean energy and the rapid development of power sales companies, large energy users, such as data centers, are given the option to buy electricity. According to electricity price, cleanliness and other factors, we can buy energy from different energy suppliers to reduce energy cost and improve energy efficiency. Research shows that under the regulation of pollution index and real time electricity price, Users tend to buy more cheap and clean energy in the period of low power consumption. Therefore, on the one hand, considering the pollution index function and the real time electricity price, a multi-source electricity purchase cost model is constructed. On the other hand, considering the operating cost and potential benefit cost of energy storage, the model of charge and discharge cost of energy storage is constructed, which is referred to as the cost model of energy storage. Based on this model, a multi-source energy selection model for data center with energy storage system is established. The simulation results show that the proposed model can reduce the daily energy cost of the data center to a certain extent by synthetically optimizing the energy storage time series and multi-source energy selection. At the same time, improve the utilization of clean energy.
【作者单位】：北京邮电大学信息与通信工程学院;网络体系构建与融合北京市重点实验室(北京邮电大学);先进信息北京市实验室(北京邮电大学);中国电力科学研究院;国家电网公司;
【基金】：北京市科技计划课题(Z171100000317003)~~
【分类号】：TP308

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