Variability Reduction of Wind Power using Aggregation and Energy Storage

Atri Bera, N. Nguyen, Saad Alzahrani, Khalil Sinjari, J. Mitra
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引用次数: 1

Abstract

Integration of wind energy into the grid poses serious challenges to the system reliability due to its intermittent nature. Variability of wind can be mitigated using various methods including deployment of energy storage systems (ESS), aggregation of geographically diverse wind, and the use of flexible loads. This paper proposes a novel method for reducing the variability of wind power by both deploying ESS and aggregating geographically diverse wind production. Although the aggregation of geographically diverse wind can reduce its intermittency to some extent, the benefits of this approach are limited due to a number of factors which are discussed in this paper. ESS, on the other hand, have been widely used for variability mitigation of wind and achieving reliability targets. However, ESS projects are expensive. In this context, this paper studies the impact of reliability enhancement of a system and the reduction in storage size by aggregating wind power from geographically diverse wind farms. The proposed approach is validated by performing sequential Monte Carlo simulation (MCS) using the IEEE Reliability Test System data. Results show that aggregation of geographically diverse wind can significantly reduce the size of ESS required for improving the reliability of the system.
利用聚合和储能减少风能的可变性
风能并网由于其间歇性的特点,对系统可靠性提出了严峻的挑战。风能的可变性可以通过各种方法来缓解,包括部署储能系统(ESS),聚集不同地理位置的风能,以及使用灵活的负载。本文提出了一种通过部署ESS和聚合地理上不同的风力生产来减少风力发电可变性的新方法。尽管地理上不同的风的聚集可以在一定程度上减少其间歇性,但由于本文讨论的一些因素,这种方法的好处是有限的。另一方面,ESS已被广泛用于缓解风的变异性和实现可靠性目标。然而,ESS项目是昂贵的。在此背景下,本文研究了通过聚合来自不同地理位置的风电场的风力发电来提高系统可靠性和减少存储容量的影响。利用IEEE可靠性测试系统数据进行时序蒙特卡罗仿真(MCS),验证了该方法的有效性。结果表明,不同地理位置的风的聚集可以显著减少提高系统可靠性所需的ESS尺寸。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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