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1. Mechanism Analysis of Wind Turbine Var Oscillations

   https://doi.org/10.1109/TIE.2022.3224198  

   Fan, Lingling; Miao, Zhixin; Shah, Shahil (December 2022, IEEE Transactions on Industrial Electronics)

   Electromagnetic transient simulation of parallel-connected 4-MW type-3 wind turbines based on original equipment manufacturer's real-code turbine model shows 1.2-Hz turbine–turbine oscillations in reactive power. This letter reveals why such oscillations occur in the individual var measurement while being insignificant in the total var measurement, regardless of the varying grid impedance. We adopt two analysis approaches, i.e., open-loop single-input single-output analysis and network decomposition. These two approaches differ in their treatment of turbine–network interaction. The open-loop analysis shows that the turbine–turbine oscillation mode is due to an open-loop system pole being attracted to an open-loop system zero. Furthermore, we use a network decomposition method to explain why this mode is observable in individual vars, while not observable in the total var. The entire system of n turbines can be viewed as n decoupled circuits. For the two-turbine case, the system has an aggregated mode and a turbine–turbine oscillation mode. The aggregated mode is associated with a circuit associated with the total var, while the turbine–turbine oscillation mode is associated with the var difference and is insensitive to the grid parameters. 

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2. Performance optimization of a wind turbine column for different incoming wind turbulence

   https://doi.org/10.1016/j.renene.2017.05.046  

   Santhanagopalan, V.; Rotea, M.A.; Iungo, G.V. (February 2018, Renewable Energy)

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3. REUSING COMPOSITE MATERIALS FROM DECOMMISSIONED WIND TURBINE BLADES

   Bank, L.C.; Arias, F.A.; Gentry, T.R.; Al-Haddadd, T.; Chen, J-F; Morrow, R (November 2017, Non-Conventional Materials and Technologies NOCMAT 2017)

   The very rapid growth in wind energy technology in the last 15 years has led to a rapid growth in the amount of non–biodegradable, thermosetting FRP composite materials used in wind turbine blades that will need to be managed of in the near future. A typical 2.0 MW turbine with three 50 m blades has approximately 20 tonnes of FRP material and an 8 MW turbine has approximately 80 tonnes of FRP material (1 MW ~ 10 tonnes of FRP). Calculations show that 4.2 million tonnes will need to be managed globally by 2035 and 16.3 million tonnes by 2055 if wind turbine construction continues at current levels and with current technology. Three major categories of end-of-life (EOL) options are possible – disposal, recovery and reuse. Reuse options are the primary focus of this paper since landfilling and incineration are environmentally harmful and recovery recycling methods are not economical. The current work reports on different architectural and structural options for reusing parts of wind turbine blades in new or retrofitted housing projects. Large-sized FRP pieces that can be salvaged from the turbine blades and potentially useful in infrastructure projects where harsh environmental conditions (water and high humidity) exist. Their noncorrosive properties make them durable construction materials. The approach presented is to cut the decommissioned wind turbine blades into segments that can be repurposed for structural and architectural applications for affordable housing projects. The geographical focus of the designs presented in this paper is in the coastal region of the Yucatan on the Gulf of Mexico where low quality masonry block informal housing is vulnerable to severe hurricanes and flooding. In what follows, a prototype 100m long wind blade model provided by Sandia National Laboratories is used as a demonstration to show how a wind blade can be broken down into parts, thus making it possible to envision architectural applications for the different wind blade segments. 

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4. RE-WIND: Architectural Design Studio and the Re-Purposing of Wind Turbine Blades

   Morrow, R.; Gentry, R.; Al-Haddad, T. (September 2018, SEEDS 2018: Sustainable Ecological Engineering Design for Society)

   This paper discusses the opening moves of an international multidisciplinary research project involving researchers from Ireland, Northern Ireland and the US, aiming to address the global problem of end-of-life disposal of wind turbine blades. The problem is one of enormous scale on several levels: a typical 2.0 MW turbine has three 50m long blades containing around 20 tonnes of fibre reinforced plastic (FRP). It is estimated that by 2050, 39.8 million tonnes of material from the global wind industry will await disposal. Whilst land-fill is the current means of disposal, the nature of the materials used in the composite construction of wind blades (glass and carbon fibres, resins, foams) means it unsustainable. Hence, the project sets out to deploy innovative design and logistical concepts for reusing and recycling these blades. The project begins within an innovative joint design studio, staged between Queen’s University Belfast and the Georgia Institute of Technology, where architecture students will, within the highly-constrained contexts of the blade properties and the potential reuse sites, systematically generate, filter, and prototype a selection of proposals, reusing the decommissioned wind turbine blades in buildings, infrastructure, landscape, and public art. The paper analyzes the potential and challenges of considering this highly constrained and yet multidisciplinary problem within the context of a Masters level Architecture studio. The paper concludes with an analysis of how outcome-driven design problems challenge traditional design studio cultures, acknowledging the need to make processes and ideas more explicit in order to categorise, analyse, rank and refine proposed architectural solutions. 

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5. Cluster analysis of wind turbine wakes measured through a scanning Doppler wind LiDAR

   https://doi.org/10.2514/6.2021-1181  

   Maulik, Romit; Rao, Vishwas; Renganathan, S. Ashwin; Letizia, Stefano; Iungo, Giacomo Valerio (January 2021, AIAA Scitech 2021 Forum)

   null (Ed.)

   Wind turbine wakes are responsible for power losses and added fatigue loads of wind turbines. Providing capabilities to predict accurately wind-turbine wakes for different atmospheric conditions and turbine settings with low computational requirements is crucial for the optimization of wind-farm layout, and for improving wind-turbine controls aiming to increase annual energy production (AEP) and reduce the levelized cost of energy (LCOE) for wind power plants. In this work, wake measurements collected with a scanning Doppler wind Li- DAR for broad ranges of the atmospheric static stability regime and incoming wind speed are processed through K-means clustering. For computational feasibility, the cluster analysis is performed on a low-dimensional embedding of the collected data, which is obtained through proper orthogonal decomposition (POD). After data compression, we perform K-means of the POD modes to identify cluster centers and corresponding members from the LiDAR data. The different cluster centers allow us to visualize wake variability over ranges of atmospheric, wind, and turbine parameters. The results show that accurate mapping of the wake variability can be achieved with K-means clustering, which represents an initial step to develop data-driven wake models for accurate and low-computational-cost simulations of wind farms. 

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