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储能系统技术 储能系统 ★ 5.0

考虑时空负荷调节的可持续互联网数据中心灵活储能系统与可再生能源规划

Flexible Energy Storage System and Renewable Energy Planning for Sustainable Internet Data Center Considering Temporal and Spatial Load Regulation

作者 Tong Wan · Jing Qiu · Yuechuan Tao · Shuying Lai · Renjie Mao
期刊 IEEE Transactions on Industry Applications
出版日期 2025年5月
技术分类 储能系统技术
技术标签 储能系统
相关度评分 ★★★★★ 5.0 / 5.0
关键词 可持续发展 互联网数据中心 电池储能系统 可再生能源 碳排放
语言:

中文摘要

鉴于人们对环境问题的担忧与日俱增,可持续发展理念已深入人心。随着互联网数据中心(IDC)的计算负载持续增加,它们已成为电力行业的一种新型用电负荷。然而,如果数据中心依靠主要由化石燃料供电的电网运行,尤其是当能源来自热力发电机时,它们会间接导致碳排放。本文提出了一种将电池储能系统(BESS)与可再生能源规划相结合的方法,重点进行时空负荷调整,以减少数据中心的碳排放,推动其实现绿色计算。我们引入了碳强度演变公式和改进的碳排放流(CEF)方法,以衡量和监测数据中心的间接碳排放。为应对可再生能源接入所固有的波动性和不确定性,我们引入了一种精细的电压偏差风险评估方法,利用高斯混合模型(GMM)评估电压偏差的概率密度函数(PDF)。此外,我们通过引入“后悔成本”指标,开发了一种考虑长期不确定性的灵活规划模型。我们的综合方法使数据中心能够有效应对可再生能源接入的复杂性,提供一种具有韧性的能源解决方案,既能应对即时运营风险,又能应对不断变化的能源格局带来的战略挑战。

English Abstract

Given the growing concerns over environmental issues, the idea of sustainable development has gained traction. As the computational load in Internet Data Centers (IDCs) continues to increase, they have become a new type of electricity load in the power sector. Yet, if IDCs operate on an electricity grid powered primarily by fossil fuels, they indirectly contribute to carbon emissions, especially if the energy is sourced from thermal generators. This article suggests a combined approach of battery energy storage systems (BESS) and renewable energy planning, focusing on spatial and temporal load adjustments to reduce carbon emissions and promote eco-friendly computation in IDCs. We introduce a formula for carbon intensity evolution and a modified carbon emission flow (CEF) to measure and monitor the IDCs’ indirect carbon emissions. To address the inherent volatility and uncertainty of renewable energy integration, we introduce a sophisticated approach for voltage deviation risk assessment. Utilizing Gaussian Mixture Models (GMM) to evaluate the Probability Density Function (PDF) of voltage deviations. Furthermore, we develop a flexible planning model that incorporates long-term uncertainties by introducing a ‘regret cost’ metric. Our comprehensive approach enables IDCs to effectively navigate the complexities of renewable integration, delivering a resilient energy solution that addresses both the immediate operational risks and the strategic challenges posed by the evolving energy landscape.
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SunView 深度解读

该研究的时空负荷调节与储能-可再生能源协同规划技术对阳光电源PowerTitan大型储能系统和iSolarCloud云平台具有重要应用价值。数据中心场景的灵活储能配置方法可直接应用于ST系列储能变流器的容量优化设计,通过时间维度的削峰填谷和空间维度的多站点协同调度,提升储能系统经济性。该研究提出的可再生能源消纳策略可增强SG系列光伏逆变器与储能系统的协同控制能力,优化MPPT算法在波动性负荷下的响应特性。时空负荷预测与优化配置模型可集成至iSolarCloud平台,为数据中心、工商业园区等高载能场景提供智能化储能规划与运维方案,助力实现碳中和目标。