109673 20240319080949.0 doi 10.3390/en15020460 sideral 127615 ART-2022-127615 eng Cebollero, José Antonio (orcid)0000-0002-1629-6083 A survey of islanding detection methods for microgrids and assessment of non-detection zones in comparison with grid codes 2022 Access copy available to the general public Unrestricted Detection of unintentional islanding is critical in microgrids in order to guarantee personal safety and avoid equipment damage. Most islanding detection techniques are based on monitoring and detecting abnormalities in magnitudes such as frequency, voltage, current and power. However, in normal operation, the utility grid has fluctuations in voltage and frequency, and grid codes establish that local generators must remain connected if deviations from the nominal values do not exceed the defined thresholds and ramps. This means that islanding detection methods could not detect islanding if there are fluctuations that do not exceed the grid code requirements, known as the non-detection zone (NDZ). A survey on the benefits of islanding detection techniques is provided, showing the advantages and disadvantages of each one. NDZs size of the most common passive islanding detection methods are calculated and obtained by simulation and compared with the limits obtained by ENTSO-E and islanding standards in the function of grid codes requirements in order to compare the effectiveness of different techniques and the suitability of each one. info:eu-repo/grantAgreement/EC/H2020/783158/EU/first and euRopEAn siC eigTh Inches pilOt liNe/REACTION This project has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No H2020 783158-REACTION info:eu-repo/semantics/openAccess by http://creativecommons.org/licenses/by/3.0/es/ 3.2 2022 ENERGY & FUELS 80 / 119 = 0.672 2022 Q3 T3 0.632 2022 Engineering (miscellaneous) 2022 Q1 Electrical and Electronic Engineering 2022 Q2 Energy (miscellaneous) 2022 Q2 Renewable Energy, Sustainability and the Environment 2022 Q2 Fuel Technology 2022 Q2 Control and Optimization 2022 Q2 Energy Engineering and Power Technology 2022 Q2 5.5 2022 info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Cañete, David Universidad de Zaragoza (orcid)0000-0002-7008-7610 Martín-Arroyo, Susana Universidad de Zaragoza García-Gracia, Miguel Universidad de Zaragoza (orcid)0000-0002-5727-5705 Leite, Helder 5009 535 Universidad de Zaragoza Dpto. Ingeniería Eléctrica Área Ingeniería Eléctrica 15, 2 (2022), 460 [30 pp] ENERGIES Energies 1996-1073 4393696 http://zaguan.unizar.es/record/109673/files/texto_completo.pdf Versión publicada 2677351 http://zaguan.unizar.es/record/109673/files/texto_completo.jpg?subformat=icon icon Versión publicada oai:zaguan.unizar.es:109673 articulos driver 2024-03-18-12:50:00 ARTICLE