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1. Structural analysis of FRP parts from waste wind turbine blades for building reuse applications

   Lawrence C. Bank, Franco R. (September 2019, Advances in Engineering Materials, Structures and Systems: Innovations, Mechanics and Applications)

   The focus of this work is on the problem of the future waste to be generated by the decom-missioning of wind farms and especially the Fiber Reinforced Polymer (FRP) composite materials used in the wind turbine blades. The FRP composites used to manufacture the blades are not biodegradable and present severe problems with regard to waste management and their End-of-Life (EOL). The impact on polymers on the environment and society has become a major concern in many countries. With the increased awareness of the environmental impacts of climate change, decreased and more expensive natural resources, and greater global concerns for health, the barriers to FRP production and waste disposal are likely to increase. In the context of the circular economy the preferred method to manage FRP waste is to use it in new applications or processes. Recent structural analysis research conducted by the authors related to reuse of FRP composite material parts from decommissioned wind turbine blades in infrastructure applications is presented in this paper. 

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2. Wind Turbine Gearbox Failure Detection Through Cumulative Sum of Multivariate Time Series Data

   https://doi.org/10.3389/fenrg.2022.904622  

   Latiffianti, Effi; Sheng, Shawn; Ding, Yu (May 2022, Frontiers in Energy Research)

   The wind energy industry is continuously improving their operational and maintenance practice for reducing the levelized costs of energy. Anticipating failures in wind turbines enables early warnings and timely intervention, so that the costly corrective maintenance can be prevented to the largest extent possible. It also avoids production loss owing to prolonged unavailability. One critical element allowing early warning is the ability to accumulate small-magnitude symptoms resulting from the gradual degradation of wind turbine systems. Inspired by the cumulative sum control chart method, this study reports the development of a wind turbine failure detection method with such early warning capability. Specifically, the following key questions are addressed: what fault signals to accumulate, how long to accumulate, what offset to use, and how to set the alarm-triggering control limit. We apply the proposed approach to 2 years’ worth of Supervisory Control and Data Acquisition data recorded from five wind turbines. We focus our analysis on gearbox failure detection, in which the proposed approach demonstrates its ability to anticipate failure events with a good lead time. 

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3. High Fidelity Dynamic Modeling and Control of Power Regenerative Hydrostatic Wind Turbine Test Platform

   https://doi.org/10.1115/FPMC2018-8900  

   Mohanty, Biswaranjan; Stelson, Kim A. (September 2018, High Fidelity Dynamic Modeling and Control of Power Regenerative Hydrostatic Wind Turbine Test Platform)

   Conventional wind turbines are equipped with multi-stage fixed-ratio gearboxes to transmit power from the low speed rotor to the high speed generator. Gearbox failure is a major issue causing high maintenance costs. With a superior power to weight ratio, a hydrostatic transmission (HST) is an ideal candidate for a wind turbine drivetrain. HST, a continuous variable transmission, has the advantage of delivering high power with a fast and accurate response. To evaluate the performance of the HST wind turbine, a power regenerative hydrostatic wind turbine test platform has been developed. A hydraulic power source is used to emulate the dynamics of the turbine rotor. The test platform is an effective tools to validate the control strategies of the HST wind turbine. This paper presents the high fidelity mathematical model of the test platform. The parameters of the dynamic equations are identified by the experiments. The steady state and transient operations results are compared with the experimental data. The detailed control architecture of the start-up and shut-down cycle is described for the test platform. 

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4. Sustainability Implications of Current Approaches to End-of-Life of Wind Turbine Blades—A Review

   https://doi.org/10.3390/su151612557  

   Delaney, Emma L.; Leahy, Paul G.; McKinley, Jennifer M.; Gentry, T. Russell; Nagle, Angela J.; Elberling, Jeffrey; Bank, Lawrence C. (August 2023, Sustainability)

   In recent years, the sustainability of wind power has been called into question because there are currently no truly sustainable solutions to the problem of how to deal with the non-biodegradable fibre-reinforced polymer (FRP) composite wind blades (sometimes referred to as “wings”) that capture the wind energy. The vast majority of wind blades that have reached their end-of-life (EOL) currently end up in landfills (either in full-sized pieces or pulverized into smaller pieces) or are incinerated. The problem has come to a head in recent years since many countries (especially in the EU) have outlawed, or expect to outlaw in the near future, one or both of these unsustainable and polluting disposal methods. An increasing number of studies have addressed the issue of EOL blade “waste”; however, these studies are generally of little use since they make predictions that do not account for the manner in which wind blades are decommissioned (from the time the decision is made to retire a turbine (or a wind farm) to the eventual disposal or recycling of all of its components). This review attempts to lay the groundwork for a better understanding of the decommissioning process by defining how the different EOL solutions to the problem of the blade “waste” do or do not lead to “sustainable decommissioning”. The hope is that by better defining the different EOL solutions and their decommissioning pathways, a more rigorous research base for future studies of the wind blade EOL problem will be possible. This paper reviews the prior studies on wind blade EOL and divides them into a number of categories depending on the focus that the original authors chose for their EOL assessment. This paper also reviews the different methods chosen by researchers to predict the quantities of future blade waste and shows that depending on the choice of method, predictions can be different by orders of magnitude, which is not good as this can be exploited by unscrupulous parties. The paper then reviews what different researchers define as the “recycling” of wind blades and shows that depending on the definition, the percentage of how much material is actually recycled is vastly different, which is also not good and can be exploited by unscrupulous parties. Finally, using very recent proprietary data (December 2022), the paper illustrates how the different definitions and methods affect predictions on global EOL quantities and recycling rates. 

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5. Applying Hidden Markov Processes to Optimizing Power Systems Maintenance

   Wang, T.; Shittu, E. (January 2022, Proceedings of the IISE Annual Conference & Expo 2022)

   Ellis, K; Ferrell, W.; Knapp, J. (Ed.)

   Failure identification and prediction in a power system are essential components that are prerequisites for optimizing the maintenance of the system. The incidences of power system failures have increased dramatically in recent times due to the uncertainties inherent in the advent of both man-made and natural disasters. This problem is further exacerbated due to the increasing demand for higher operational efficiency in power systems. Currently, there is a paucity of studies that predict and identify failure in a distribution power system. In this paper, we propose an integrated methodology for selecting the optimal maintenance plan based on predicting and identifying failure modes with the aid of Hidden Markov Models (HMM) and a probabilistic decision-making tool. While the model parameters of previous studies were determined utilizing observable prior knowledge, the use of HMM offers a different approach especially in the absence of such observable prior distributions. Thus, we determine the status of health of a power system by using an HMM to capture the relationship between unobservable degradation state and observed parameters. The preliminary outcome is instructive for the management of power systems especially in response to fortifying the system against aging and degradation. 

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