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优化储能容量以增强韧性:海上风电场案例
Optimizing energy storage capacity for enhanced resilience: The case of offshore wind farms
| 作者 | Weijie Pan · Ekundayo Shitt |
| 期刊 | Applied Energy |
| 出版日期 | 2025年1月 |
| 卷/期 | 第 378 卷 |
| 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 | Offshore wind farm network topologies impact energy storage capacity decisions. |
语言:
中文摘要
摘要 本文研究了在面对导致短期至中期停电的高影响低概率(HILP)事件时,不同海上风电场(OWF)网络配置对电池储能系统(BESS)最优容量的影响。由于占地面积较小且能源产出潜力较高,大规模海上风电场近年来受到投资者越来越多的关注。然而,外部环境、内部安装结构以及距离陆上设施较远等因素给海上风电场的运行和能源供应稳定性带来了重大挑战。这些因素使得系统极易受到HILP突发事件的影响,而灾后及时管理(例如修复海底输电电缆故障)也极为困难。尽管BESS长期以来被视为提升系统韧性的可行策略,但关于确定最优BESS容量的决策过程仍缺乏深入研究,尤其是在考虑多种OWF拓扑结构的情况下,这些拓扑结构会显著影响能源供应效率,进而影响BESS的稳定运行。本研究采用基于“规划+运行”顺序建模的方法,整合了凝聚层次聚类(AHC)、最优OWF网络配置算法、随机系统故障场景生成方法以及最优BESS容量模型。通过该方法,推导出对应于不同聚类层级的最优BESS容量综合分布特征。将所提出的模型应用于三个不同的海上风电场案例,得出能够在增强系统韧性与经济性之间实现平衡的最优BESS容量。在本研究的建模设定背景下,该最优容量约为满发状态下日发电量的16%(不包括容量系数)。最优BESS容量不仅标准化并促进了更具韧性的海上风电场在应对短期和中期系统故障时的设计流程,还为政策制定者提供了依据,以考虑并实施协调利用海上风电场能源与其他可用发电技术的市场策略。本研究填补了海上风电场拓扑结构研究与系统韧性讨论之间的学术空白,并揭示了最优BESS容量与理想聚类数量之间的关系。
English Abstract
Abstract 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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SunView 深度解读
该研究对阳光电源ST系列储能变流器及PowerTitan系统在海上风电场景具有重要指导意义。论文提出的16%日发电量最优储能容量配置方法,可直接应用于我司海上风电储能解决方案设计。建议结合我司GFM控制技术和iSolarCloud平台的预测性维护功能,针对海上风电HILP事件开发专用储能容量优化算法,提升系统韧性。该拓扑优化与储能配置协同方法可融入PowerTitan产品线,形成差异化竞争优势,特别适用于远海大规模风电项目的EPC总包方案。