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- Genre: Academic theses
Description
Wind measurements are fundamental inputs for the evaluation of potential energy yield and performance of wind farms. Three-dimensional scanning coherent Doppler lidar (CDL) may provide a new basis for wind farm site selection, design, and control. In this research, CDL measurements obtained from multiple wind energy developments are analyzed and a novel wind farm control approach has been modeled. The possibility of using lidar measurements to more fully characterize the wind field is discussed, specifically, terrain effects, spatial variation of winds, power density, and the effect of shear at different layers within the rotor swept area. Various vector retrieval methods have been applied to the lidar data, and results are presented on an elevated terrain-following surface at hub height. The vector retrieval estimates are compared with tower measurements, after interpolation to the appropriate level. CDL data is used to estimate the spatial power density at hub height. Since CDL can measure winds at different vertical levels, an approach for estimating wind power density over the wind turbine rotor-swept area is explored. Sample optimized layouts of wind farm using lidar data and global optimization algorithms, accounting for wake interaction effects, have been explored. An approach to evaluate spatial wind speed and direction estimates from a standard nested Coupled Ocean and Atmosphere Mesoscale Prediction System (COAMPS) model and CDL is presented. The magnitude of spatial difference between observations and simulation for wind energy assessment is researched. Diurnal effects and ramp events as estimated by CDL and COAMPS were inter-compared. Novel wind farm control based on incoming winds and direction input from CDL's is developed. Both yaw and pitch control using scanning CDL for efficient wind farm control is analyzed. The wind farm control optimizes power production and reduces loads on wind turbines for various lidar wind speed and direction inputs, accounting for wind farm wake losses and wind speed evolution. Several wind farm control configurations were developed, for enhanced integrability into the electrical grid. Finally, the value proposition of CDL for a wind farm development, based on uncertainty reduction and return of investment is analyzed.
ContributorsKrishnamurthy, Raghavendra (Author) / Calhoun, Ronald J (Thesis advisor) / Chen, Kangping (Committee member) / Huang, Huei-Ping (Committee member) / Fraser, Matthew (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
Description
Understanding and predicting climate changes at the urban scale have been an important yet challenging problem in environmental engineering. The lack of reliable long-term observations at the urban scale makes it difficult to even assess past climate changes. Numerical modeling plays an important role in filling the gap of observation and predicting future changes. Numerical studies on the climatic effect of desert urbanization have focused on basic meteorological fields such as temperature and wind. For desert cities, urban expansion can lead to substantial changes in the local production of wind-blown dust, which have implications for air quality and public health. This study expands the existing framework of numerical simulation for desert urbanization to include the computation of dust generation related to urban land-use changes. This is accomplished by connecting a suite of numerical models, including a meso-scale meteorological model, a land-surface model, an urban canopy model, and a turbulence model, to produce the key parameters that control the surface fluxes of wind-blown dust. Those models generate the near-surface turbulence intensity, soil moisture, and land-surface properties, which are used to determine the dust fluxes from a set of laboratory-based empirical formulas. This framework is applied to a series of simulations for the desert city of Erbil across a period of rapid urbanization. The changes in surface dust fluxes associated with urbanization are quantified. An analysis of the model output further reveals the dependence of surface dust fluxes on local meteorological conditions. Future applications of the models to environmental prediction are discussed.
ContributorsTahir, Sherzad Tahseen (Author) / Huang, Huei-Ping (Thesis advisor) / Phelan, Patrick (Committee member) / Herrmann, Marcus (Committee member) / Chen, Kangping (Committee member) / Clarke, Amanda (Committee member) / Arizona State University (Publisher)
Created2019