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The expansion of wind power around the world poses a new challenge that network operators must overcome, namely the integration of this renewable energy source into the grid. Comprehensive analyses involving time-domain simulations must be carried out to plan network operation and ensure power supply. In light of the above, and with the aim of extending the use of the wind turbine models developed by Standard IEC 61400-27-1 and assessing their performance according to national grid code requirements, an IEC Type 3 wind turbine model has been submitted for the first time to Spanish grid code PO 12.3. Indeed, there is a lack of studies submitting generic wind turbine models to national grid code requirements. The model's behavior is compared with field measurements of an actual Gamesa G52 machine and with its detailed simulation model. The outcomes obtained have been comprehensively analyzed and the results of the validation criteria highlight that several modeling modifications, in the cases of non-compliance, must be implemented in the IEC-developed Type 3 model in order to comply with PO 12.3. Nevertheless, the results also show that when the transformer inrush current is not considered, the reactive power response of the generic Type 3 WT model meets the validation criteria, thus complying with Spanish PO 12.3. ; This research was funded by the Spanish Ministry of Economy and Competitiveness and European Union FEDER, grant number ENE2016-78214-C2-1-R, as well as the Agreement signed between the UCLM and the Council of Albacete to foster Research in the Campus of Albacete. The authors would also like to express their gratitude to the wind turbine manufacturer Siemens Gamesa Renewable Energy for the technical support received. Furthermore, the authors would like to thank the TC 88/WG 27 Committee "Wind turbines Electrical simulation models for wind power generation", to his Convenor, Poul Sørensen, and to the 16 participating countries.

(c) 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other users, including reprinting/ republishing this material for advertising or promotional purposes, creating new collective works for resale or redistribution to servers or lists, or reuse of any copyrighted components of this work in other works. ; [EN] While wind turbine (WT) power capacities continue to increase and new offshore developments are being deployed, operation and maintenance (O&M) costs continue to rise, becoming the center of attention in the wind energy sector. The electric generator is among the top three contributors to failure rates and downtime of WTs, where the doubly fed induction generator (DFIG) is the dominant technology among variable speed WTs. Thus, the early detection of generator faults, which can be achieved through predictive maintenance, is vital in order to reduce O&M costs. The goal of this paper is to analyze a long-term monitoring campaign of an in-service WT equipped with a DFIG. A novel method named the harmonic order tracking analysis is used with two main objectives: first, to facilitate the data interpretation for non-trained maintenance personnel, and second, to reduce the amount of data that must be stored and transferred for the diagnosis of the DFIG. This method is applied and validated for the first time on an operating WT. ; This work was supported in part by the Agreement signed between the UCLM and the Council of Albacete to promote research in the Campus of Albacete, and in part by the European Union Horizon 2020 Research and Innovation Programme through the Marie Sklodowska-Curie Grant (AWESOME Project) under Grant 642108. The authors would like to thank Ingeteam Power Technology S.A. UP Service, part of the AWESOME Project Consortium providing the wind turbine data. ; Artigao, E.; Sapena-Bano, A.; Honrubia-Escribano, A.; Martinez-Roman, J.; Puche-Panadero, R.; Gómez-Lázaro, E. (2019). Long-Term Operational Data Analysis of an In-Service Wind ...

Wind power plants are becoming a generally accepted resource in the generation mix of many utilities. At the same time, the size and the power rating of individual wind turbines have increased considerably. Under these circumstances, the sector is increasingly demanding an accurate characterization of vertical wind speed profiles to estimate properly the incoming wind speed at the rotor swept area and, consequently, assess the potential for a wind power plant site. The present paper describes a shape-based clustering characterization and visualization of real vertical wind speed data. The proposed solution allows us to identify the most likely vertical wind speed patterns for a specific location based on real wind speed measurements. Moreover, this clustering approach also provides characterization and classification of such vertical wind profiles. This solution is highly suitable for a large amount of data collected by remote sensing equipment, where wind speed values at different heights within the rotor swept area are available for subsequent analysis. The methodology is based on z-normalization, shape-based distance metric solution and the Ward-hierarchical clustering method. Real vertical wind speed profile data corresponding to a Spanish wind power plant and collected by using a commercialWindcube equipment during several months are used to assess the proposed characterization and clustering process, involving more than 100000 wind speed data values. All analyses have been implemented using open-source R-software. From the results, at least four different vertical wind speed patterns are identified to characterize properly over 90% of the collected wind speed data along the day. Therefore, alternative analytical function criteria should be subsequently proposed for vertical wind speed characterization purposes. ; The authors are grateful for the financial support from the Spanish Ministry of the Economy and Competitiveness and the European Union —ENE2016-78214-C2-2-R—and the Spanish Education, Culture and Sport Ministry —FPU16/0428