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arXiv 1904.04771eess.SYcs.SYmath.OC
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为可靠地整合可再生能源进行存储容量设计:一种大偏差方法

Sizing Storage for Reliable Renewable Integration: A Large Deviations Approach

Indian Institute of Technology Bombay(印度孟买理工学院)

Vivek Deulkar, Jayakrishnan Nair, Ankur A. Kulkarni

AI总结:

本文提出了一种基于大偏差理论的方法,用于确定可再生能源与储能系统结合时的存储容量,以提高电力系统的可靠性,并通过实际案例验证了该方法的实用性。

摘要:

风能和太阳能发电的固有间歇性给我们在提高可再生能源在电网中的渗透率带来了重大挑战。越来越多的能源存储系统被部署在可再生能源发电旁边以应对这种间歇性。然而,文献中缺乏对由存储系统与可再生能源发电结合后可靠性正式表征的描述。本文旨在填补这一空白。我们使用马尔可夫调节流队列模型来建模可再生能源发电与电池结合时的负荷损失概率(LOLP),以应对不确定的需求过程。进一步,我们表征了电池规模趋于无穷大时LOLP的渐进行为。我们的结果揭示了可实现可靠性的根本限制,并指导了为满足给定可靠性目标所需的存储容量的确定。最后,我们使用实际的风能数据进行案例研究,以展示我们的结果在实践中的适用性。

英文摘要:

The inherent intermittency of wind and solar generation presents a significant challenge as we seek to increase the penetration of renewable generation in the power grid. Increasingly, energy storage is being deployed alongside renewable generation to counter this intermittency. However, a formal characterization of the reliability of renewable generators bundled with storage is lacking in the literature. The present paper seeks to fill this gap. We use a Markov modulated fluid queue to model the loss of load probability (LOLP) associated with a renewable generator bundled with a battery, serving an uncertain demand process. Further, we characterize the asymptotic behavior of the LOLP as the battery size scales to infinity. Our results shed light on the fundamental limits of reliability achievable, and also guide the sizing of the storage required in order to meet a given reliability target. Finally, we present a case study using real-world wind power data to demonstrate the applicability of our results in practice.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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