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Wind turbine gearboxes do not achieve their expected design life. The cost of gearbox replacements and rebuilds and the downtime associated with these failures increase the cost of wind energy. In 2007, the U.S. Department of Energy established the National Renewable Energy Laboratory (NREL) Gearbox Reliability Collaborative (GRC). Its goals are to understand the root causes of premature gearbox failures and improve their reliability. To date, the GRC has focused on a 750-kW drivetrain with a three-stage, three-point-mounted gearbox. A nonproprietary version of the gearbox containing CRBs with C3 clearances in the planetary stage was customized. Two of these gearboxes, GB1 and GB2, were manufactured and then tested in the National Wind Technology Center's 2.5-MW dynamometer and in the field. Major GRC findings include the detrimental effect of rotor moments on planetary load sharing and predicted fatigue, and the risk of bearing sliding in low-torque conditions for three-point configuration drivetrains. Based on the knowledge gained from testing and analysis of the original design, the GRC gearbox was redesigned to improve its load-sharing characteristics and predicted fatigue. This new gearbox is named GB3. As shown in Figure 1, its key improvement is the incorporation of preloaded TRBs that support the planet carrier and planets. Roller loads can be optimized and bearing life maximized with a small preload [4]. These preloaded bearings, along with interference-fitted planet pins, improve alignments and load-sharing characteristics. A semi-integrated planet bearing design also increases capacity and eliminates outer race fretting. Romax Technology, with Powertrain Engineers and the Timken Company (Timken), completed the redesign. Timken manufactured and instrumented the planet gears and bearings. Brad Foote Gearing manufactured the other gearing and assembled the gearbox.
This presentation describes a system dynamics simulation (SD) framework that supports an end-to-end analysis workflow that is optimized for deployment on ESIF facilities(Peregrine and the Insight Center). It includes (I) parallel and distributed simulation of SD models, (ii) real-time 3D visualization of running simulations, and (iii) comprehensive database-oriented persistence of simulation metadata, inputs, and outputs.
Innovation clusters have been important for recent development of clean energy technologies and their emergence as mature, globally competitive industries. However, the factors that influence the co-location of manufacturing activities with innovation clusters are less clear. A central question for government agencies seeking to grow manufacturing as part of economic development in their location is how innovation clusters influence manufacturing. Thus, this paper examines case studies of innovation clusters for three different clean energy technologies that have developed in at least two locations: solar PV clusters in California and the province of Jiangsu in China, wind turbine clusters in Germany and the U.S. Great Lakes region, and ethanol clusters in the U.S. Midwest and the state of Sao Paulo in Brazil. These case studies provide initial insight into factors and conditions that contribute to technology manufacturing facility location decisions.
Output data from an NREL report entitled "An Assessment of the Economic Potential of Offshore Wind in the United States from 2015 to 2030" (NREL/TP-6A20-67675), which analyzes the spatial variation of levelized cost of energy (LCOE) and levelized avoided cost of energy (LACE) to understand the economic potential of fixed-bottom and floating offshore wind technologies across more than 7,000 U.S. coastal sites between 2015 and 2030.
This presentation provides an overview of findings from a report published in 2016 by researchers at the National Renewable Energy Laboratory, An Initial Evaluation of Siting Considerations on Current and Future Wind Deployment. The presentation covers the background for research, the Energy Department's Wind Vision, research methods, siting considerations, the wind project deployment process, and costs associated with siting considerations.
The global wind industry has witnessed exciting developments in recent years. The future will be even brighter with further reductions in capital and operation and maintenance costs, which can be accomplished with improved turbine reliability, especially when turbines are installed offshore. One opportunity for the industry to improve wind turbine reliability is through the exploration of reliability engineering life data analysis based on readily available data or maintenance records collected at typical wind plants. If adopted and conducted appropriately, these analyses can quickly save operation and maintenance costs in a potentially impactful manner. This chapter discusses wind turbine reliability by highlighting the methodology of reliability engineering life data analysis. It first briefly discusses fundamentals for wind turbine reliability and the current industry status. Then, the reliability engineering method for life analysis, including data collection, model development, and forecasting, is presented in detail and illustrated through two case studies. The chapter concludes with some remarks on potential opportunities to improve wind turbine reliability. An owner and operator's perspective is taken and mechanical components are used to exemplify the potential benefits of reliability engineering analysis to improve wind turbine reliability and availability.
A novel short-term state forecasting-based optimal power flow (OPF) approach for distribution system voltage regulation is proposed in this paper. An extreme learning machine (ELM) based state forecaster is developed to accurately predict system states (voltage magnitudes and angles) in the near future. Based on the forecast system states, a dynamically weighted three-phase AC OPF problem is formulated to minimize the voltage violations with higher penalization on buses which are forecast to have higher voltage violations in the near future. By solving the proposed OPF problem, the controllable resources in the system are optimally coordinated to alleviate the potential severe voltage violations and improve the overall voltage profile. The proposed approach has been tested in a 12-bus distribution system and simulation results are presented to demonstrate the performance of the proposed approach.