Wind energy research: State-of-the-art and future research directions

Association, 2012 2008 Bolinger, 2009, Wind power price trends in the United States: struggling to remain competitive in the face of strong growth, Energy Policy, 37, 1061, 10.1016/j.enpol.2008.10.053 Albadi, 2010, Overview of wind power intermittency impacts on power systems, Electr. Power Syst. Res., 80, 627, 10.1016/j.epsr.2009.10.035 Cavallo, 2007, Controllable and affordable utility-scale electricity from intermittent wind resources and compressed air energy storage (CAES), Energy, 32, 120, 10.1016/j.energy.2006.03.018 Sovacool, 2009, The intermittency of wind, solar, and renewable electricity generators: technical barrier or rhetorical excuse?, Util. Policy, 17, 288, 10.1016/j.jup.2008.07.001 Spinato, 2009, Reliability of wind turbine subassemblies, IET Renew. Power Gener., 3, 387, 10.1049/iet-rpg.2008.0060 Walford, 2006 Faulstich, 2011, Wind turbine downtime and its importance for offshore deployment, Wind Energy, 14, 327, 10.1002/we.421 Boyle, 2012 Piwko, 2006, Integrating large wind farms into weak power grids with long transmission lines Perveen, 2014, Off-shore wind farm development: present status and challenges, Renew. Sustain. Energy Rev., 29, 780, 10.1016/j.rser.2013.08.108 Barlas, 2010, Review of state of the art in smart rotor control research for wind turbines, Prog. Aerosp. Sci., 46, 1, 10.1016/j.paerosci.2009.08.002 Bossanyi, 2012, Advanced controller research for multi-MW wind turbines in the UPWIND project, Wind Energy, 15, 119, 10.1002/we.523 Márquez, 2012, Condition monitoring of wind turbines: techniques and methods, Renew. Energy, 46, 169, 10.1016/j.renene.2012.03.003 Hameed, 2009, Condition monitoring and fault detection of wind turbines and related algorithms: a review, Renew. Sustain. energy Rev., 13, 1, 10.1016/j.rser.2007.05.008 Blaabjerg, 2013, Future on power electronics for wind turbine systems, IEEE J. Emerg. Sel. Top. Power Electron., 1, 139, 10.1109/JESTPE.2013.2275978 Hossain, 2016, Role of smart grid in renewable energy: an overview, Renew. Sustain. Energy Rev., 60, 1168, 10.1016/j.rser.2015.09.098 Milligan, 2015 Jacobson, 2015, Low-cost solution to the grid reliability problem with 100% penetration of intermittent wind, water, and solar for all purposes, Proc. Natl. Acad. Sci., 112, 15060, 10.1073/pnas.1510028112 Larcher, 2015, Towards greener and more sustainable batteries for electrical energy storage, Nat. Chem., 7, 19, 10.1038/nchem.2085 Polinder, 2007, 10 MW wind turbine direct-drive generator design with pitch or active speed stall control Griffith, 2013 González, 2010, Optimization of wind farm turbines layout using an evolutive algorithm, Renew. Energy, 35, 1671, 10.1016/j.renene.2010.01.010 Musial, 2004, Future for offshore wind energy in the United States Wayman, 2006, Coupled dynamic modeling of floating wind turbine systems Fleming, 2013, The SOWFA super-controller: a high-fidelity tool for evaluating wind plant control approaches Hansen, 2006, Centralised power control of wind farm with doubly fed induction generators, Renew. Energy, 31, 935, 10.1016/j.renene.2005.05.011 Moné, 2015 Lantz, 2013 Mandell, 2010 Riddle, 2012, Effects of defects: Part A-Development of a protocol for defect risk management & improved reliability of composite structures Woo, 2013, Effects of defects: Part B—Progressive damage modeling of fiberglass/epoxy composite structures with manufacturing induced flaws utilizing cohesive zone elements Riddle, 2011, Characterization of manufacturing defects common to composite wind turbine blades: flaw characterization Lambert, 2012, 3D damage characterisation and the role of voids in the fatigue of wind turbine blade materials, Compos. Sci. Technol., 72, 337, 10.1016/j.compscitech.2011.11.023 Zhou, 2014, A review of full-scale structural testing of wind turbine blades, Renew. Sustain. Energy Rev., 33, 177, 10.1016/j.rser.2014.01.087 Wiser, 2014 Johnson, 2016 Smith, 2015 Fingersh, 2006 Nati, 2013, Control of vortex shedding from a blunt trailing edge using plasma actuators, Exp. Therm. Fluid Sci., 46, 199, 10.1016/j.expthermflusci.2012.12.012 Oerlemans, 2009, Reduction of wind turbine noise using optimized airfoils and trailing-edge serrations, AIAA J., 47, 1470, 10.2514/1.38888 Wolf, 2015, Trailing edge noise reduction of wind turbine blades by active flow control, Wind Energy, 18, 909, 10.1002/we.1737 Leventhal, 2013 ACMA. Certification - American Composites Manufacturers Association (ACMA). Last accessed 8/26/16]; Available from: http://www.acmanet.org/cct. 2015 Loth, 2017, Downwind pre-aligned rotors for extreme-scale wind turbines, Wind Energy, 20, 1241 Jay, 2016, 30 Bagamiel, 2017, Integrated design and manufacturing approach for a faster and easier production of rotor blade molds Gardiner, 2013, Modular design eases big wind blade assembly, Compos. Technol., 8 Gruhn, 2012, Rodpack: a new form of aliged fiber reinforcement for wind blade spar caps Baran, 2014, Pultrusion of a vertical axis wind turbine blade part-I: 3D thermo-chemical process simulation, Int. J. Mater. Form., 8, 379, 10.1007/s12289-014-1179-6 Baran, 2014, Pultrusion of a vertical axis wind turbine blade part-II: combining the manufacturing process simulation with a subsequent loading scenario, Int. J. Mater. Form., 8, 367, 10.1007/s12289-014-1178-7 Pastine, 2012, Can epoxy composites be made 100% recyclable?, Reinf. Plast., 56, 26, 10.1016/S0034-3617(12)70109-1 Beauson, 2014, Recycling solid residues recovered from glass fibre-reinforced composites – a review applied to wind turbine blade materials, J. Reinf. Plast. Compos., 33, 1542, 10.1177/0731684414537131 Witik, 2013, Carbon fibre reinforced composite waste: an environmental assessment of recycling, energy recovery and landfilling, Compos. Part A Appl. Sci. Manuf., 49, 89, 10.1016/j.compositesa.2013.02.009 Wei, 2016, Toward performance-based evaluation for offshore wind turbine jacket support structures, Renew. Energy, 97, 709, 10.1016/j.renene.2016.06.028 Wei, 2016, Toward performance-based evaluation for offshore wind turbine jacket support structures, Renew. Energy, 97, 709, 10.1016/j.renene.2016.06.028 Hallowell, 2016, Site-specific variability of load extremes of offshore wind turbines exposed to hurricane risk and breaking waves, Wind Energy, 20, 143, 10.1002/we.1996 Wei, 2016, Directional effects on the reliability of non-axisymmetric support structures for offshore wind turbines under extreme wind and wave loadings, Eng. Struct., 106, 68, 10.1016/j.engstruct.2015.10.016 Hallowell, 2016, Variability of breaking wave characteristics and impact loads on offshore wind turbines supported by monopiles, Wind Energy, 19, 301, 10.1002/we.1833 Wei, 2014, Incremental wind-wave analysis of the structural capacity of offshore wind turbine support structures under extreme loading, Eng. Struct., 79, 58, 10.1016/j.engstruct.2014.08.010 2016, AWEA U.S wind industry annual market report year ending 2015 Valamanesh, 2015, Multivariate analysis of extreme metocean conditions for offshore wind turbines, Struct. Saf., 55, 60, 10.1016/j.strusafe.2015.03.002 Valamanesh, 2016, Wind-wave prediction equations for probabilistic offshore hurricane hazard analysis, Nat. Hazards, 83, 541, 10.1007/s11069-016-2331-z DeepwaterWind. Block Island Wind Farm - Deepwater Wind. [Last accessed 8/26/16]; Available from: http://dwwind.com/project/block-island-wind-farm/. Sheng, 2013, Report on wind turbine subsystem reliability ─ a survey of various databases Sheng, 2015, Improving component reliability through performance and condition monitoring data analysis 2015 Haberlein, 2016 Bruce, 2015, Characterisation of white etching crack damage in wind turbine gearbox bearings, Wear, 338–339, 164, 10.1016/j.wear.2015.06.008 Greco, 2013, Material wear and fatigue in wind turbine systems, Wear, 302, 1583, 10.1016/j.wear.2013.01.060 Herr, D., Heidenreich, D., Understanding the root causes of axial cracking in wind turbine gearbox bearings. AeroTorque Technical Notes http://www.AeroTorque.com. Keller, 2015 Sheng, S., Guo, Y., An Integrated Approach Using Condition Monitoring and Modeling to Investigate Wind Turbine Gearbox Design. National Renewable Energy Laboratory, NREL/CP-5000–60978. Yi, 2015, Dynamic modeling and analysis of load sharing characteristics of wind turbine gearbox, Adv. Mech. Eng., 7, 10.1177/1687814015575960 Antoniadou, 2015, A time–frequency analysis approach for condition monitoring of a wind turbine gearbox under varying load conditions, Mech. Syst. Signal Process., 64–65, 188, 10.1016/j.ymssp.2015.03.003 Jain, 2011, A dynamic model to predict the occurrence of skidding in wind-turbine bearings, J. Phys. Conf. Ser., 305, 012027, 10.1088/1742-6596/305/1/012027 McNiff, 2014 Guo, 2013, Model fidelity study of dynamic transient loads in a wind turbine gearbox Schkoda, 2014, Geartrain reduction for real-time simulation of a multibody wind turbine gearbox model Fyler, 2016, A dynamic Model for double-planet planetary gearsets, J. Vib. Acoust., 138, 10.1115/1.4032181 Fyler, 2017, A design framework to improve the dynamic characteristics of double planet planetary gearsets, vol. 8, 405 GE. Condition Monitoring and Vibration Equipment - GE Bently Nevada. Last accessed 8/26/16]; Available from: https://www.gemeasurement.com/condition-monitoring-and-protection. Gram&Juhl. Gram & Juhl. Last accessed 8/26/16]; Available from: http://gramjuhl.com. BachmannElectronic. Bachmann Electronic GmbH | Condition Monitoring System. Last accessed 8/26/16]; Available from: http://www.bachmann.info/en/products/condition-monitoring-system. BoschRexroth. Condition Monitoring System - Bosch Rexroth. Last accessed 8/26/16]; Available from: https://www.boschrexroth.com/en/us/service/service-by-market/renewable-energies/service-products/condition-monitoring-system/index. Wolfel. Wolfel - Condition Monitoring. Last accessed 8/26/16]; Available from: http://www.woelfel.de/en/industries/mechanical-and-shyelectrical-engineering/condition-monitoring.html. Needelman, 2009, Contamination control for wind turbine gearboxes, Power Eng., 113 Ragheb, 2010, Wind turbine gearbox technologies Keller, 2012 Lucas, 2005, Planet Pac: Increasing Epicyclic Power Density and Performance through Integration (AGMA 05FTM18) Fox, 2008 Manwell, 2009 Yan, 2016, Study on dynamic characteristic of wind turbine emulator based on PMSM, Renew. Energy, 97, 731, 10.1016/j.renene.2016.06.034 Inc, T. [cited 2017 August 2nd ]; Available from: https://www.timken.com/products/timken-engineered-bearings/tapered-roller/. Froese Moventus. [cited 2017 August 2nd]; Available from: https://www.moventas.com/wp-content/uploads/2017/05/Case-Carburizing.pdf. AeroTorque. Available from: https://www.aerotorque.com/sites/default/files/0-AeroTorque Feb 2016 full reprint.pdf. Science, S.; Available from: http://sentientscience.com/products/- digitalclone-live. RomaxWind. Available from: https://www.romaxtech.com/software/romaxwind/. Ansol. Available from: http://www.ansol.us/Products/TX3/. Sirnivas, 2014 2002 Commission, I.E, 2009, 3 Commission, I.E, 2009 IEC, 2001, 4 2012 2013 Wind, 2005 Structural, 2011, vol. 305 Jonkman, 2010, Offshore code comparison collaboration (OC3) for IEA task 23 offshore wind technology and deployment, Contract, 303, 275 Energy, A., Alternate Uses of Existing Facilities on the Outer Continental Shelf. The Federal Register/FIND73. 132. Carswell, 2015, Soil–structure reliability of offshore wind turbine monopile foundations, Wind Energy, 18, 483, 10.1002/we.1710 Estate, T.C.; Available from: http://www.marinedataexchange.co.uk/. MEDIN. Available from: http://www.oceannet.org/. Pryor, 2011, Assessing climate change impacts on the near-term stability of the wind energy resource over the USA, Proc. Natl. Acad. Sci., 108, 8167, 10.1073/pnas.1019388108 Wosnik, 2013, Velocity deficit and swirl in the turbulent wake of a wind turbine, Mar. Technol. Soc. J., 47, 193, 10.4031/MTSJ.47.4.20 Hasager, 2005, Offshore wind resource assessed from satellite SAR wind field maps, Wind Energy, 8, 403, 10.1002/we.150 Sathe, 2013, A review of turbulence measurements using ground-based wind lidars. Atmos, Meas. Tech. Discuss., 6, 6815 Mikkelsen, 2013, A spinner-integrated wind lidar for enhanced wind turbine control, Wind Energy, 16, 625, 10.1002/we.1564 Barthelmie, 2013, Meteorological controls on wind turbine wakes, Proc. IEEE, 101, 1010, 10.1109/JPROC.2012.2204029 Barthelmie, 2014, 3D wind and turbulence characteristics of the atmospheric boundary-layer, Bull. Am. Meteorol. Soc., 95, 743, 10.1175/BAMS-D-12-00111.1 Pentalum. Pentalum Technologies - Remote Wind Measurements LiDAR. Last accessed 8/16/16]; Available from: http://pentalum.com/. Manwell, 2007, Review of design conditions applicable to offshore wind energy systems in the United States, Renew. Sustain. Energy Rev., 11, 210, 10.1016/j.rser.2005.01.002 Pryor, 2013, Assessing the vulnerability of wind energy to climate change and extreme events, Clim. Change, 121, 79, 10.1007/s10584-013-0889-y Pryor, 2012, Past and future wind climates over the contiguous USA based on the NARCCAP model suite, J. Geophys. Res., 117 Sandia. SWiFT Facility & Testing. Last Accessed 8/27/2016]; Available from: http://energy.sandia.gov/energy/renewable-energy/wind-power/wind_plant_opt/. Prediction of Extreme Wind Speed at Wind Energy Sites, a Set of Guidelines Prepared under ETSU Contract W/11/00427/00. National Wind Power and Climatic Research Unit of the University of East Anglia. Vickery, 2000, Simulation of hurricane risk in the US using empirical track model, J. Struct. Eng., 126, 1222, 10.1061/(ASCE)0733-9445(2000)126:10(1222) Booij, 1996, The “SWAN” wave model for shallow water, Coast. Eng. Proc., 1 Booij, 1999, A third-generation wave model for coastal regions: 1. model description and validation, J. Geophys. Res. Oceans, 104, 7649, 10.1029/98JC02622 Ris, 1999, A third-generation wave model for coastal regions: 2. verification, J. Geophys. Res. Oceans, 104, 7667, 10.1029/1998JC900123 Curcic, 2013, Coupled atmosphere-waveocean modeling to characterize hurricane load cases for offshore wind turbines Chen, 2007, The CBLAST-Hurricane program and the next-generation fully coupled atmosphere–wave–ocean models for hurricane research and prediction, Bull. Am. Meteorol. Soc., 88, 311, 10.1175/BAMS-88-3-311 Chen, 2013, Directional wind–wave coupling in fully coupled atmosphere–wave–ocean models: results from CBLAST-Hurricane, J. Atmos. Sci., 70, 3198, 10.1175/JAS-D-12-0157.1 Skamarock, 2008, A time-split nonhydrostatic atmospheric model for weather research and forecasting applications, J. Comput. Phys., 227, 3465, 10.1016/j.jcp.2007.01.037 Donelan, 2012, Modeling waves and wind stress, J. Geophys. Res. Oceans, 117, 10.1029/2011JC007787 Wallcraft, 2009 Kim, 2014, Hurricane-induced loads on offshore wind turbines with considerations for nacelle yaw and blade pitch control, Wind Eng., 38, 413, 10.1260/0309-524X.38.4.413 Storm, 2009, Evaluation of the weather research and forecasting model on forecasting low-level jets: implications for wind energy, Wind Energy, 12, 81, 10.1002/we.288 Dominion. Virginia Offshore Wind Technology Advancement Project. Last accessed 8/16/16]; Available from: https://www.dom.com/corporate/what-we-do/electricity/generation/wind/virginia-offshore-wind-technology-advancement-project. Boezaart, 2014 Bossanyi, 2003 Bentley. SACS Offshore Structure Design and Analysis Software. Last accessed 8/27/16]; Available from: https://www.bentley.com/en/products/product-line/offshore-structural-analysis-software/sacs-offshore-structure. Renkema, 2007 Ishihara, 2004, Development of a new wake model based on a wind tunnel experiment, Glob. wind power, 1 Frandsen, 2006, Analytical modelling of wind speed deficit in large offshore wind farms, Wind energy, 9, 39, 10.1002/we.189 Katic, 1986, A simple model for cluster efficiency Bossanyi, 2003, Individual blade pitch control for load reduction, Wind energy, 6, 119, 10.1002/we.76 Garcia-Gonzalez, 2008, Stochastic joint optimization of wind generation and pumped-storage units in an electricity market, IEEE Trans. Power Syst., 23, 460, 10.1109/TPWRS.2008.919430 Gebraad, 2016, Wind plant power optimization through yaw control using a parametric model for wake effects—a CFD simulation study, Wind Energy, 19, 95, 10.1002/we.1822 Pieter M. O. Gebraad, J. W. van Wingerden, A Control-Oriented Dynamic Model for Wakes in Wind Plants, Published under licence by IOP Publishing Ltd Journal of Physics: Conference Series, vol. 524, conference 1. Chinchilla, 2006, Control of permanent-magnet generators applied to variable-speed wind-energy systems connected to the grid, IEEE Trans. energy Convers., 21, 130, 10.1109/TEC.2005.853735 Muljadi, 2001, Pitch-controlled variable-speed wind turbine generation, IEEE Trans. Ind. Appl., 37, 240, 10.1109/28.903156 Attia, 2012 Santoni, 2015, Development of a high fidelity CFD code for wind farm control Iungo, 2016, Reduced order model for optimization of power production from a wind farm, 34th Wind Energy Symp., 10.2514/6.2016-2200 DiPaola, 2016, A fast differential deficit control volume approach for modeling turbine-turbine interactions Yang, 2015, Optimizing energy capture of cascaded wind turbine array with nested-loop extremum seeking control, J. Dyn. Syst. Meas. Control, 137, 121010, 10.1115/1.4031593 Ciri, 2016, Large eddy simulation for an array of turbines with extremum seeking control Lackner, 2011, Structural control of floating wind turbines, Mechatronics, 21, 704, 10.1016/j.mechatronics.2010.11.007 Heier, 2014 Griffith, 2015 GmbH, 2007 Sharma, 2013, Condition monitoring of wind turbines: a review, Glob. J. Res. Eng. Mech. Mech. Eng., 13 Sheng, 2011 Fischer, K. and D. Coronado, Condition monitoring of wind turbines: state of the art, user experience and recommendations. Pierretchakoua, 2015, 283 Paquette, 2016 Paquette, J., NDI, EoD, and SHM to improve blade reliability, in Presentation at the UMass Lowell Wind Energy Research Workshop. Lowell, MA. Vaisala. Vaisala - Lightning Explorer. Last accessed 8/26/16]; Available from: http://thunderstorm.vaisala.com/explorer.html. Roach, 2012 Sohn, 2003 Doebling, 1996 Griffith, 2015 Fox, 1992, 522 Salawu, 1997, Detection of structural damage through changes in frequency: a review, Eng. Struct., 19, 718, 10.1016/S0141-0296(96)00149-6 Kim, 1992, Application of the modal assurance criteria for detecting and locating structural faults, 536 Niezrecki, 2014, Wind turbine blade health monitoring using acoustic beamforming techniques Lindberg, 2014, Ground based inspection of wind turbine blades Post, 2016, Improving bending moment measurements on wind turbine blades Sandia. Continuous Reliability Enhancement for Wind (CREW) Database and Analysis Program. Last Accessed 8/27/2016]; Available from: http://energy.sandia.gov/energy/renewable-energy/wind-power/materials-reliability-standards/continuous-reliability-enhancement-for-wind-crew-database/. Newman, 2014 Meinlschmidt, 2006, Thermographic inspection of rotor blades Poozesh, 2016, Structural health monitoring of wind turbine blades using acoustic microphone array, Struct. Health Monit. Niezrecki, 2014, Wind turbine blade health monitoring using acoustic beamforming techniques, J. Acoust. Soc. Am., 135, 2392, 10.1121/1.4877915 Navigant. Available from: https://www.navigantresearch.com/research/drones-for-wind-turbine-inspection. Crabtree, 2011 Dunn, 2011, Electrical energy storage for the grid: a battery of choices, Science, 334, 928, 10.1126/science.1212741 Pearre, 2015, Technoeconomic feasibility of grid storage: mapping electrical services and energy storage technologies, Appl. Energy, 137, 501, 10.1016/j.apenergy.2014.04.050 Stenzel, 2016, Concept and potential of pumped hydro storage in federal waterways, Appl. energy, 162, 486, 10.1016/j.apenergy.2015.10.033 Jílek, 2015, Electricity storage systems using compressed air. in electric power engineering (EPE) Madlener, 2013, Economics of centralized and decentralized compressed air energy storage for enhanced grid integration of wind power, Appl. Energy, 101, 299, 10.1016/j.apenergy.2011.09.033 Mahlia, 2014, vol. 33, 532 Díaz-González, 2012, 2154 Poullikkas, 2013, vol. 27, 778 Bruce, 2012, Li-O2 and Li-S batteries with high energy storage, Nat. Mater., 11, 19, 10.1038/nmat3191 Alotto, 2014, Redox flow batteries for the storage of renewable energy: a review, Renew. Sustain. Energy Rev., 29, 325, 10.1016/j.rser.2013.08.001 Dennison, 2016, Enhancing mass transport in redox flow batteries by tailoring flow field and electrode design. Journal of the Electrochemical Society, 163, A5163 Henninger, 2017, New materials for adsorption heat transformation and storage, Renew. Energy, 110, 59, 10.1016/j.renene.2016.08.041 Yang, 2016, Graphene-based materials with tailored nanostructures for energy conversion and storage, Mater. Sci. Eng. R Rep., 102, 1, 10.1016/j.mser.2015.12.003 Luo, 2015, Overview of current development in electrical energy storage technologies and the application potential in power system operation, Appl. Energy, 137, 511, 10.1016/j.apenergy.2014.09.081 Boicea, 2014, Energy storage technologies: the past and the present, Proc. IEEE, 102, 1777, 10.1109/JPROC.2014.2359545 Liu, 2013, Addressing the grand challenges in energy storage, Adv. Funct. Mater., 23, 924, 10.1002/adfm.201203058 Sakti, 2015, A techno-economic analysis and optimization of Li-ion batteries for light-duty passenger vehicle electrification, J. Power Sources, 273, 966, 10.1016/j.jpowsour.2014.09.078 Takagi, 2013, Economic value of PV energy storage using batteries of battery-switch stations, IEEE Trans. Sustain. Energy, 4, 164, 10.1109/TSTE.2012.2210571 Killingsworth, 2011, Increased efficiency in SI engine with air replaced by oxygen in argon mixture, Proc. Combust. Inst., 33, 3141, 10.1016/j.proci.2010.07.035 Darling, 2014, Pathways to low-cost electrochemical energy storage: a comparison of aqueous and nonaqueous flow batteries, Energy & Environ. Sci., 7, 3459, 10.1039/C4EE02158D Kaufman, 2011, Electricity storage in regulated markets: getting the rules right, The Electr. J., 24, 63, 10.1016/j.tej.2011.06.006