Power system dynamic analysis in future energy scenarios with high penetration of renewable energy sources — case study: Sicilian electrical grid

IF 4.8 2区 工程技术 Q2 ENERGY & FUELS
Rossano Musca , Eleonora Riva Sanseverino , Gaetano Zizzo , Antony Vasile , Adriano Iaria , Angelo L’Abbate , Lorenzo Vitulano
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引用次数: 0

Abstract

In the near future, Sicily will undergo an unprecedented penetration of renewable sources in its electricity generation mix. In response to these developments, several grid enhancement initiatives have been planned, including HVDC infrastructure and interconnections with foreign systems. This paper presents the results of dynamic studies on 2030 energy scenarios developed by the Italian institute Ricerca Sistema Energetico (RSE). These studies consider severe contingencies and evaluate various combinations of regulating resources, both traditional and innovative, including Grid Forming control. The results indicate that relying solely on traditional regulation during contingencies leads to instability, emphasizing the urgent need to involve all available resources in the power system’s regulation mechanisms. Among the most interesting findings is the case of the Grid Forming control applied to the Tyrrhenian Link: even in the absence of regulation from the renewable sources present on the island, this approach successfully keeps the frequency drift within the permissible 1.5 Hz range. This demonstrates the significant strategic value of the infrastructure when deployed to provide dynamic support to the power system.
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来源期刊
Sustainable Energy Grids & Networks
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.
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