Browsing by Author "Lee, Duehee"
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Item Design and implementation of three-phase inverters using a TMS320F2812 digital signal processor(2009-12) Lee, Duehee; Santoso, Surya; Grady, Mack W.The goal of this thesis project was to design and build a three-phase inverter controlled by the TMS320F2812 DSP by Texas Instruments. The TMS320F2812 is controlled in order to make inverters generate output waveforms which mimic the main reference signal coming from a computer. The project included building three different inverters on two platforms including auxiliary circuits and designing five pulse width modulation (PWM) switching algorithms for the inverters. The motivation was that a newly designed inverter was required as an intermediary device between a computer and a laboratory-scaled model of a wind turbine. This type of wind turbine is used to educate students and engineers and to extract experimental wind power data. However, since commercial inverters don’t follow the main reference signal which is sent from the computer in order to operate the laboratory-scaled wind turbine, a controllable and variable inverter needed to be designed to receive that signal. The results are as follows. The voltage source inverter (VSI) and the current-controlled voltage source inverter (CC-VSI) were built on the VSI platform, and the current source inverter (CSI) was built on the CSI platform. Furthermore, the TMS320F2812’s analog digital converter (ADC) driver circuit and the output LC filter were also designed as auxiliary circuits. Five PWM switching programs were written; three switching algorithms for the VSI, and one algorithm each for the CC-VSI and the CSI. The output waveforms from the combination of hardware and software mentioned above were captured, and they follow the main reference signal very well. Although each of the inverters performed well, the VSI in combination with the Space Vector PWM switching algorithm produced the cleanest output voltage waveforms with the least amount of noise. The inverters built in this thesis project can be applied to the laboratory-scaled wind turbine, the maximum power tracking in solar panels, and equipment for analyzing digital signal processing. However, before using the inverters in those applications, much work remains to be done to solve the problems related to the signal distortion caused by the dead band time, harmonic signals caused by the fixed switching frequency, and the reliability issues caused by mounting on the bread board. In conclusion, although this thesis does not illustrate the entire process of or explain every requirement for building the three inverters, enough information about the topology of the inverters, the hardware design, and the PWM switching algorithms is provided in this thesis to enable one to remake all three of the three-phase inverters.Item Wind power forecasting and its applications to the power system(2015-05) Lee, Duehee; Baldick, Ross; Santoso, Surya; Arapostathis, Aristotle; Webber, Michael; Morton, DavidThe goal of research in this dissertation is to bring more wind resources into the power grid by mitigating the uncertainty of the current wind power, by developing a new algorithm to respond to the fluctuation of the future wind power, and by building additional transmission lines to bring more wind resources from a remote area to the load center. First, in order to overcome the wind power uncertainty, the probabilistic and ensemble wind power forecasting is proposed to increase the forecasting accuracy and to deliver the probability density function of the uncertainty. Accurate wind power forecasting reduces the amounts and cost of ancillary services (AS). As the mismatch between the bid and actual amount of delivered energy decreases, the imbalance between supply and demand also decreases. If the forecasting ahead is increased up to 24 hours, accurate wind power forecasting can also help wind farm owners bid the exact amount of wind power in the day ahead (DA) market. Furthermore, wind power owners can use the parametric probabilistic density of error distributions for hedging the price risk and building a better offer curve. Second, a novel algorithm to generate many wind power scenarios as a function of installed capacity of wind power is proposed based on an analysis of the power spectral density of wind power. Scenarios can be used to simulate the power system to estimate the required amount of AS to respond to the fluctuation of future wind power as the installed capacity of wind power increases. Scenarios have statistical characteristics of the future wind power that are regressed as a function of the installed capacity of wind power from the statistical characteristics of the current wind power. This algorithm can generate many possible scenarios to simulate the power system in many different situations. Third, optimal transmission expansion by simulating the power system with the multiple load and wind power scenarios in different locations is planned to prepare the preliminary result to bring more wind resources in remote areas to the load center in Texas. In this process, the geographical smoothing effects of wind power and the stochastic correlation structure between the load and wind power are considered. Furthermore, the generalized dynamic factor model (GDFM) is used to synthesize load and wind power scenarios to keep their correlation structure. The premise of the GDFM is that a few factors can drive the correlated movements of load and wind power simultaneously, so the scenario generation process is parsimonious.