Optimal inertia allocation in future transmission networks: A case study on the Italian grid

IF 5.6 2区工程技术 Q2 ENERGY & FUELS Sustainable Energy Grids & Networks Pub Date : 2025-03-05 DOI:10.1016/j.segan.2025.101676

Manuela Minetti , Matteo Fresia , Renato Procopio , Andrea Bonfiglio , Gio Battista Denegri , Giuseppe Lisciandrello , Luca Orrù

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Abstract

The paper introduces a technical-economic methodology to estimate the additional inertia required in a Transmission Network for future scenarios and presents an algorithm to optimally dispatch it among different sources and interwork busbars. First, the amount of inertia is calculated to constrain the Rate of Change of Frequency (RoCoF) within sustainable limits. Then, such inertia is allocated accounting for the contributions from Renewable Energy Sources (RESs) and Battery Energy Storage Systems (BESSs), complemented by the deployment of Synchronous Compensators (SCs) across various nodes of a Transmission Network. The methodology underwent testing within the Italian Transmission Network, utilizing the informational support furnished by the Italian Transmission System Operator (TSO). Despite its simplicity, the results exhibit notable accuracy, validated through rigorous comparisons with detailed time-domain simulations. Moreover, the low computational cost of the method, allowed a statistical analysis considering all the hours of year 2030, to get information on the distributions of the quantities of interest.

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未来输电网络的最佳惯性分配：以意大利电网为例

本文介绍了一种技术经济方法来估计未来情况下传输网络所需的额外惯性，并提出了一种在不同源和互连母线之间最佳调度的算法。首先，计算惯性量以将频率变化率（RoCoF）限制在可持续范围内。然后，根据可再生能源（RESs）和电池储能系统（BESSs）的贡献分配这种惯性，并在输电网络的各个节点上部署同步补偿器（SCs）。利用意大利输电系统运营商（TSO）提供的信息支持，该方法在意大利输电网络内进行了测试。尽管它很简单，但通过与详细的时域模拟的严格比较，结果显示出显著的准确性。此外，该方法的计算成本低，允许考虑2030年所有小时的统计分析，以获得有关感兴趣数量分布的信息。

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来源期刊

Sustainable Energy Grids & Networks Energy-Energy Engineering and Power Technology

CiteScore

7.90

自引率

13.00%

发文量

206

审稿时长

49 days

期刊介绍： Sustainable Energy, Grids and Networks (SEGAN)is an international peer-reviewed publication for theoretical and applied research dealing with energy, information grids and power networks, including smart grids from super to micro grid scales. SEGAN welcomes papers describing fundamental advances in mathematical, statistical or computational methods with application to power and energy systems, as well as papers on applications, computation and modeling in the areas of electrical and energy systems with coupled information and communication technologies.