优化储能能力,提高复原力:海上风电场案例

IF 10.1 1区 工程技术 Q1 ENERGY & FUELS
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引用次数: 0

摘要

本文研究了在高影响低概率(HILP)事件导致中短期停电的情况下,海上风电场(OWF)网络的不同配置对电池储能系统(BESS)最佳容量的影响。大规模 OWF 因其较小的占地面积和较高的能源生产潜力而日益受到投资者的关注。然而,外部环境、内部安装以及与陆上设施的距离较远,都对海上风电场的运行和能源供应的稳定性构成了巨大挑战。这些因素导致系统极易受到 HILP 突发事件的影响,而及时的灾后管理(如处理海底输电电缆故障)也极具挑战性。虽然 BESS 长期以来一直被认为是提高系统恢复能力的可行策略,但对确定最佳 BESS 容量的决策过程却缺乏深入探讨。当考虑到多种多样的 OWF 拓扑结构时,这种情况就更加明显,因为这些拓扑结构会严重影响能源供应效率,进而影响 BESS 的稳定运行。本研究采用了一种基于 "规划 + 运行 "顺序建模方法,该方法集成了聚合分层聚类(AHC)、最佳 OWF 网络配置算法、随机系统故障情景生成方法和最佳 BESS 容量模型。得出了与不同聚类水平相对应的最佳 BESS 容量综合概况。将所提出的模型应用于三种不同的 OWF 案例,得出了最佳 BESS 容量,同时兼顾了弹性增强和经济因素。在本研究的建模设置中,最佳容量约为满负荷日发电量的 16%(不包括容量因子)。最佳 BESS 容量不仅规范和促进了设计更能抵御中短期系统故障的开放式风能发电设备的过程,还为政策制定者提供了考虑和实施协调使用开放式风能发电设备能源和市场上其他可用发电技术的战略的基础。本研究弥补了 OWF 拓扑研究与系统恢复能力讨论之间的研究空白,同时阐明了最佳 BESS 容量与理想集群数量之间的关系。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimizing energy storage capacity for enhanced resilience: The case of offshore wind farms
This paper investigates the influence of different configurations of the offshore wind farms (OWF) network on the optimal capacities of battery energy storage systems (BESS) in the face of high-impact low-probability (HILP) events that cause short- to medium-term outages. Large-scale OWFs have garnered increasing attention from investors due to their smaller land footprint and higher energy production potential. However, the external environment, the internal installation, and the long distance from the onshore facilities pose significant challenges to the operations of the OWFs and the stability of the energy supply. These factors render systems highly susceptible to HILP contingencies, while timely post-disaster management, such as addressing subsea transmission cable failures, is challenging. Although BESS has long been considered a viable strategy to improve the resilience of the system, the decision-making process to determine the optimal BESS capacity is underexplored. This is more pronounced when considering the diverse OWF topologies that can significantly impact energy supply efficiency and, consequently, impact the stable operation of BESS. This study employs a methodology based on sequential “planning + operational” modeling approach that integrates Agglomerative Hierarchical Clustering (AHC), an optimal OWF network configuration algorithm, a stochastic system failure scenario generation approach, and an optimal BESS capacity model. Comprehensive profiles of optimal BESS capacity are derived corresponding to different clustering levels. Applying the proposed model to three different OWF cases derived the optimal BESS capacity, balancing resilience enhancement and economic considerations. In the context of the modeling settings in this study, this optimal capacity is approximately 16% of the daily electricity generation at full capacity, excluding the capacity factor. Optimal BESS capacity not only standardizes and facilitates the design process of more resilient OWFs to short- and medium-term system failures, but also provides policymakers with a basis to consider and implement strategies to coordinate the use of OWF energy and other available power generation technologies in the market. This study bridges the research gap between OWF topology studies and discussions on system resilience while shedding light on the relationship between optimal BESS capacities and the ideal number of clusters.
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来源期刊
Applied Energy
Applied Energy 工程技术-工程:化工
CiteScore
21.20
自引率
10.70%
发文量
1830
审稿时长
41 days
期刊介绍: Applied Energy serves as a platform for sharing innovations, research, development, and demonstrations in energy conversion, conservation, and sustainable energy systems. The journal covers topics such as optimal energy resource use, environmental pollutant mitigation, and energy process analysis. It welcomes original papers, review articles, technical notes, and letters to the editor. Authors are encouraged to submit manuscripts that bridge the gap between research, development, and implementation. The journal addresses a wide spectrum of topics, including fossil and renewable energy technologies, energy economics, and environmental impacts. Applied Energy also explores modeling and forecasting, conservation strategies, and the social and economic implications of energy policies, including climate change mitigation. It is complemented by the open-access journal Advances in Applied Energy.
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