A novel robust optimization method for mobile energy storage pre-positioning

IF 10.1 1区工程技术 Q1 ENERGY & FUELS

Applied Energy Pub Date : 2024-11-20 DOI:10.1016/j.apenergy.2024.124810

Hening Yuan, Yueqing Shen, Xuehua Xie

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引用次数: 0

Abstract

The traditional power distribution network is transitioning to an active electrical distribution network due to the integration of distributed energy resources. Simultaneously, the increasing occurrence of extreme weather requires power networks to be more resilient. Distributed energy resources, especially mobile energy storage systems (MESS), play a crucial role in enhancing the resilience of electrical distribution networks. However, research is lacking on pre-positioning of MESS to enhance resilience, efficiency and electrical resource utilization in post-disaster operations. To address these issues, this paper introduces a proactive MESS pre-positioning method in active electrical distribution networks considering the uncertainties of distributed generation output. Firstly, the flexible resources in active distribution networks are modeled, including distributed generation, MESS and Electric Vehicles. Then, a robust optimization model is established for the pre-positioning of MESS considering the PV output uncertainty, where the big-M method and the column constraint generation algorithm are used to calculate the optimal capacity and location of the MESS. Finally, the effectiveness of the MESS pre-positioning model is verified using the IEEE 33-node system and the IEEE 141-node system, respectively. The simulation results show that the load loss at most of the nodes is significantly reduced and the total system cost is reduced by 17.65% compared with the case of fixed MESS access location. The results also show that when the number of MESS is low, each additional MESS unit reduces the total load shedding cost by about 20%. Moreover, the proposed robust optimization model for MESS pre-positioning is also effective in large-scale systems.

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移动储能预定位的新型稳健优化方法

由于分布式能源资源的整合，传统的配电网络正在向主动配电网络过渡。与此同时，越来越多的极端天气也要求配电网具有更强的抗灾能力。分布式能源，尤其是移动储能系统（MESS），在增强配电网的弹性方面发挥着至关重要的作用。然而，目前还缺乏对移动储能系统进行预先定位以提高灾后运行的复原力、效率和电力资源利用率的研究。针对这些问题，本文介绍了一种考虑到分布式发电输出不确定性的主动配电网 MESS 预定位方法。首先，对主动配电网中的灵活资源进行建模，包括分布式发电、MESS 和电动汽车。然后，建立了考虑光伏发电输出不确定性的 MESS 预定位鲁棒优化模型，利用 big-M 方法和列约束生成算法计算 MESS 的最优容量和位置。最后，分别使用 IEEE 33 节点系统和 IEEE 141 节点系统验证了 MESS 预定位模型的有效性。仿真结果表明，与 MESS 接入位置固定的情况相比，大部分节点的负载损耗明显降低，系统总成本降低了 17.65%。结果还显示，当 MESS 数量较少时，每增加一个 MESS 单元，总甩负荷成本就会降低约 20%。此外，所提出的 MESS 预定位稳健优化模型在大规模系统中也很有效。

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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来源期刊

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.