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Description
Lidar has demonstrated its utility in meteorological studies, wind resource assessment, and wind farm control. More recently, lidar has gained widespread attention for autonomous vehicles.
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
The first part of the dissertation begins with an application of a coherent Doppler lidar to wind gust characterization for wind farm control. This application focuses on wind gusts on a scale from 100 m to 1000 m. A detecting and tracking algorithm is proposed to extract gusts from a wind field and track their movement. The algorithm was implemented for a three-hour, two-dimensional wind field retrieved from the measurements of a coherent Doppler lidar. The Gaussian distribution of the gust spanwise deviation from the streamline was demonstrated. Size dependency of gust deviations is discussed. A prediction model estimating the impact of gusts with respect to arrival time and the probability of arrival locations is introduced. The prediction model was applied to a virtual wind turbine array, and estimates are given for which wind turbines would be impacted.
The second part of this dissertation describes a Time-of-Flight lidar simulation. The lidar simulation includes a laser source module, a propagation module, a receiver module, and a timing module. A two-dimensional pulse model is introduced in the laser source module. The sampling rate for the pulse model is explored. The propagation module takes accounts of beam divergence, target characteristics, atmosphere, and optics. The receiver module contains models of noise and analog filters in a lidar receiver. The effect of analog filters on the signal behavior was investigated. The timing module includes a Time-to-Digital Converter (TDC) module and an Analog-to-Digital converter (ADC) module. In the TDC module, several walk-error compensation methods for leading-edge detection and multiple timing algorithms were modeled and tested on simulated signals. In the ADC module, a benchmark (BM) timing algorithm is proposed. A Neyman-Pearson (NP) detector was implemented in the time domain and frequency domain (fast Fourier transform (FFT) approach). The FFT approach with frequency-domain zero-paddings improves the timing resolution. The BM algorithm was tested on simulated signals, and the NP detector was evaluated on both simulated signals and measurements from a prototype lidar (Bhaskaran, 2018).
ContributorsZhou, Kai (Author) / Calhoun, Ronald (Thesis advisor) / Chen, Kangping (Committee member) / Tang, Wenbo (Committee member) / Peet, Yulia (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2019
Description
Kuwait is committed to implementing the Kyoto Protocol in “Vision 2035” to reduce greenhouse gas emissions by shifting to the use of wind and solar energies [1]. The specific goal of the Vision 2035 is for renewables to comprise 15% of Kuwait’s electrical generation by 2030. Wind and solar are abundant in Kuwait and can easily provide 15% of the total electrical generation. However, there are three significant obstacles. The first is Kuwait currently depends heavily on rapidly diminishing fossil fuels which are the major sources of CO2, NOx, and SOx emissions. Unfortunately, current plans are to build two conventional power stations by 2024. The purpose is to cover the energy needs for growing population. The second problem is that Kuwait has a very small land area. Consequently, there is limited space to build new utility-scale renewable power stations. The third issue is the low electricity tariff provides little incentive for the population to save energy. Offshore wind farms have the potential to provide thousands of GWh/yr to accomplish the goals of Vision 2035. Kuwait has a vast untapped supply of offshore wind energy. Specifically, there are eight offshore locations in which 50 turbines could be built each, for a total of 400 turbines. Using 4.2 MW turbines, this would provide 1.68 GW of wind energy, and increase the renewable portion of the electrical energy production to 13.93% (including Shagaya renewable park). Installing battery storage with the proposed wind turbines could provide fast ramp response which would serve to complement existing power production on Kuwait’s grid. In this work, six different turbines with different sizes are considered from 2.5 MW to 4.2 MW (from well-known manufacturers, such as, Nordex and Vestas), but ultimately 4.2 MW turbines are recommended. Data for this study has been supplied by: A) Civil Aviation -- temperature and wind speed, B) Ministry of Electricity and Water (MEW) -- electricity data, and C) Public Authority for Civil Information -- population data.
ContributorsAlotaibi, Abdullah Saqer (Author) / Calhoun, Ronald (Thesis advisor) / Kitchen, Jennifer (Thesis advisor) / Roedel, Ronald (Committee member) / Mayyas, Abdul Ra'ouf (Committee member) / Arizona State University (Publisher)
Created2020