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Analytical methodology for reliability assessment of distribution networks with energy storage in islanded and emergency-tie restoration modes

机译:孤岛和紧急联络恢复模式下具有能量存储的配电网可靠性评估的分析方法

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摘要

A wide scale deployment of energy storage systems in power networks for energy balancing applications will lead to network reliability improvements. After a fault occurs in a network, energy storage will be able to help restore supply in the network areas isolated from the primary substation or in those re-connected to adjacent feeders of limited transfer capacity by emergency-ties. The reliability improvements introduced by energy storage need to be evaluated and quantified for both restoration modes. The objective of this paper is to assess the energy storage contribution in these restoration modes and to seek analytical, less computationally intensive solutions for such evaluation. The proposed analytical technique uses a probabilistic model of energy storage to assess the charge and discharge processes over a fault duration and the related operational strategy. In this way, reliability indices are calculated by taking into account the energy storage actions during a fault as well as the time-evolution of renewable generation and demand. These features lead to more realistic modelling of energy storage in analytical techniques. The proposed analytical technique was firstly validated by using a case study where the results obtained by Monte Carlo Simulation were used as a reference. Then, the proposed technique was applied to a distribution network to assess the reliability improvement provided by energy storage and to demonstrate the effectiveness and accuracy of the proposed approach.
机译:在电力网络中为能量平衡应用大规模部署能量存储系统将导致网络可靠性的提高。网络发生故障后,能量存储将能够帮助恢复与主变电站隔离的网络区域或通过紧急联系重新连接到传输能力受限的相邻馈线的网络区域的供电。对于两种恢复模式,都需要评估和量化由能量存储引入的可靠性改进。本文的目的是评估在这些恢复模式下的储能贡献,并寻求分析性,计算量较少的解决方案。所提出的分析技术使用能量存储的概率模型来评估故障持续时间内的充电和放电过程以及相关的操作策略。通过这种方式,可通过考虑故障期间的储能行为以及可再生发电和需求的时间演变来计算可靠性指标。这些功能使分析技术中的储能模型更加逼真。首先通过案例研究验证了所提出的分析技术,该案例研究将蒙特卡罗模拟获得的结果用作参考。然后,将所提出的技术应用于配电网络,以评估能量存储所提供的可靠性提高,并证明所提出方法的有效性和准确性。

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