The importance of the use of renewable energy sources is obviously. But what the problem confused us, is that renewable energy unlike the fossil fuel have such high energy density which means the renewable generally was dispersed form. In other words, in order to obtain amount of the energy we need, require to exploitation a wider cover area. Therefore, scientists and companies are struggling to find high densely renewable energy as possible, which is high altitude wind energy, have very promising but not developed so much by humans. High altitude wind power is indicating the altitude between 3000 meters and 10000 meters. So far, high altitude wind power is a new renewable energy that basically not development or utilization yet, but which is an abundant reserves. High altitude wind power is a widely distributed renewable clean energy. The characterized of high-altitude wind energy is fast speed, wide distribution, high stability and perennial. Utilize high-altitude wind power can get high stability with low cost of wind power generation, which is one of the notable features for high-altitude wind power, but also is one of the most significant advantages for high-altitude wind energy compared to conventional wind energy. High altitude wind power generation equipment is more compact and flexible, far superior then the traditional fan, which equip with thick blades and the tower must be fixed in the depths of the ocean or in the ground.To development renewable power in a large scale, to face the global climate change, achieve the sustainable development become the inevitable for human development. How to solve the energy shortage problem has become an important question, harness high altitude wind power was becomes the focus of multinational technology.

Wind energy is a proven energy source that does not contribute to emission of greenhouse gases, air and water pollution, or generate large quantities of waste. However, wind generation is dependent on wind speed, which is difficult to predict with high accuracy. The intermittent nature of wind generation makes its operation and planning a complex problem and there is a need for advanced analytical models to embed this uncertainty in its generation profile. This research focuses on the development of innovative mathematical modeling and analysis tools to improve our understanding of the effects of wind generation on power systems. The overall goal of this research is to introduce novel analytical frameworks to consider the penetration of wind generation sources within the distribution and transmission networks. In particular, two main operational problems are addressed within this thesis; the Distribution Load Flow (DLF) problem and the Unit Commitment (UC) problem in the presence of wind generation. First for the DLF problem, a novel probabilistic wind generation model is presented. The probabilistic wind generation profile, which is a function of the wind speed, is considered and an appropriate procedure is developed to classify specific levels based on wind speed, in order to reduce the number of probabilistic combinations of wind power generation. Next, a novel Probabilistic Distribution Load Flow (PDLF) approach is used to evaluate the impact of wind penetration into distribution systems. The traditional DLF program is modified to include the wind generation profiles. Three Wind Turbine (WT) models are derived and integrated within the PDLF program to examine and compare their performance. The probabilistic forward-backward sweep algorithm is developed for the first two models of WT. For the third model of WT, a probabilistic compensation-based load flow is presented. The effect of WT penetration is investigated on feeder losses, voltage profile and line flows. Secondly, a new scenario generation and reduction technique is developed for analyzing the effects of wind generation uncertainties on short-term power system operation. A historical wind speed data set is used to obtain different wind speed clusters which are then processed through Monte Carlo Simulations (MCS), Markov-chains and a forward selection scenario reduction algorithm to obtain a reduced set of scenarios. These reduced scenarios are then incorporated into a Locational Marginal Price (LMP) based electricity market settlement and dispatch model. These UC type models incorporate system constraints and transmission constraints to examine the effects of wind generation on electricity market prices, UC decisions including generation, reserve requirement, load cleared and social welfare. Markov-chain transition matrices are developed to include the effect of the inter-hour transition correlation of wind speed from one specific hour to the following hour to improve the generation of the wind scenarios. The effect of changing wind farm capacity on system operation is also discussed. Furthermore, the impact of the wake-effect phenomena influencing off-shore wind turbines is explained. Finally, this research examines the effect of wind generation penetration on the environmental emissions. A novel methodology is developed to evaluate the environmental impact of wind generation penetration into electrical power systems. The solution of the market dispatch UC model is studied for different cost functions with an emission cap. The relationship between changing the emission caps and the penetration level of wind energy is investigated. Furthermore, the effect on market prices is also examined when emission caps are imposed by external agencies, on the System Operator (SO).

No description available.

The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor speed measurements as control variable inputs. The dependence on the accuracy of the measurement devices makes the controller less reliable. The proposed control scheme is based on the stiff system concept and provides a fast response and a dynamic solution to the complicated aerodynamic system. This control scheme provides a response to the wind changes without the knowledge of wind speed and turbine parameters. The system consists of a permanent magnet synchronous machine (PMSM), a passive rectifier, a dc/dc boost converter, a current controlled voltage source inverter, and a microcontroller that commands the dc/dc converter to control the generator for maximum power extraction. The microcontroller will also be able to control the current output of the three-phase inverter. In this work, the aerodynamic characteristics of wind turbines and the power conversion system topology are explained. The maximum power tracking control algorithm with a variable step estimator is introduced and the modeling and simulation of the wind turbine generator system using the MATLAB/SIMULINK® software is presented and its results show, at least in principle, that the maximum power tracking algorithm developed is suitable for wind turbine generation systems.

The purpose of this work is to develop a maximum power tracking control strategy for variable speed wind turbine systems. Modern wind turbine control systems are slow, and they depend on the design parameters of the turbine and use wind and/or rotor speed measurements as control variable inputs. The dependence on the accuracy of the measurement devices makes the controller less reliable. The proposed control scheme is based on the stiff system concept and provides a fast response and a dynamic solution to the complicated aerodynamic system. This control scheme provides a response to the wind changes without the knowledge of wind speed and turbine parameters. The system consists of a permanent magnet synchronous machine (PMSM), a passive rectifier, a dc/dc boost converter, a current controlled voltage source inverter, and a microcontroller that commands the dc/dc converter to control the generator for maximum power extraction. The microcontroller will also be able to control the current output of the three-phase inverter. In this work, the aerodynamic characteristics of wind turbines and the power conversion system topology are explained. The maximum power tracking control algorithm with a variable step estimator is introduced and the modeling and simulation of the wind turbine generator system using the MATLAB/SIMULINK® software is presented and its results show, at least in principle, that the maximum power tracking algorithm developed is suitable for wind turbine generation systems.

The coastal current is influenced by coastline topography, its advection direction is parallel with coastline because different periodic of wind field function makes the ocean dynamics is more complicated in coastal. In order to treat the effects of topography and wind to coastal current variations, we make long time observation data about ocean and meteorology and analyze them near the harbor of HSinDa in Kaohsiung . This research use bottom Acoustic Doppler Current Profiler (bm-ADCP ) , Temperature and Pressure Logger(TP ) , anemometer and wind direction vane to observe flow field ,tidal and wind field in the locality. The collected data are analyzed through a variety of time series analysis technique , such as strain wave, harmonic analysis , Fast Fourior Transform (FFT) analysis that uses different frequency wave bands make an relevant analysis materials and then. The results show that (1) when sea-land breeze was weak, the main axial angle of diurnal tide ellipticity of the current was parallel with the coastline direction. Because the friction of sea flow affected; the ellipticity became smaller and assumed the reciprocal motion¡Fwhen sea-land breeze was stronger, diurnal tide ellipticity of the current was bigger, and main axial angle from coastline parallel changes to follow the sea-land breeze heading. It means sea-land breeze can affect the surface flow motion. (2)When a front passed in winter, it produces the current faced to the southeast along the coast. In the energy spectrum effect, the wind field and the flow field have the same peak of the period, the period was 4 days, 5.5 days, and 8 days, it means that the correlation of the flow field and wind field is good; this result is closed with the observes in land station. (3)In the period of southwest monsoon, there has coastal current toward northwest in the southwest of Taiwan straits. In the other period, the direction of current always moved toward southeast. The result of the low-frequency filter, the flow is smaller than tidal current and wind-drift current. It means that this sea area is affected by tide current and wind-drift current.

Thesis (M.S.)--James Madison University, 2009. / Includes bibliographical references.

Wind energy development and its stigma of avian mortality provide a case for exploring the complexities that can occur between science, law, politics, and planning. The present method of measuring mortality appears flawed and may hamper the ability of resource agencies, the public, and industry in making educated decisions about siting wind farms and protecting species. The U.S. Fish and Wildlife Service has the ability to take an active role and affect a project already constructed. The Migratory Bird Treaty Act appears to keep the issue of avian mortality within the minds of wind energy developers. Protecting species on the brink of extinction is codified in the Endangered Species Act, which seems to be well suited for protecting most species. The significance of avian mortality can be linked to public perceptions. The industry in Texas has taken the approach of not sharing avian-related data, except in very few instances. Providing such substantial federal incentives through the Production Tax Credit rather than direct federal funding bypasses the National Environmental Policy Act and its requirement that federal governments consider impacts to the environment. / text

This dissertation addresses the modeling of wind turbine systems (WTS) and wind farms. The WTS reliability model provides the generation state space of a WTS. The generation states are derived from the combinations of the wind states from given wind data and the condition states of each component in a WTS. Wake effect is accounted when there are neighboring WTSs. The results of the reliability model of a WTS are associated with the generation states of the WTS, which include the probability, transition rates to other states, frequency of transitions to other states, and duration. The reliability model of the wind farm is derived by combining the wind states, WTS states and the distribution line states. The results of the reliability model of a wind farm are associated with the generation states of the wind farm, which include the probability, transition rates to other states, frequency to other states, and duration. The reliability model of the wind turbine system and the reliability model of the wind farm presented in this dissertation bring contribution to the planning and operation of bulk power systems with wind farm integration. The developed models can provide the system operator with clear reliability indices in terms of generation states of wind turbine systems and wind farms along with their probability, duration and frequency of transitions.

Wind energy is a proven energy source that does not contribute to emission of greenhouse gases, air and water pollution, or generate large quantities of waste. However, wind generation is dependent on wind speed, which is difficult to predict with high accuracy. The intermittent nature of wind generation makes its operation and planning a complex problem and there is a need for advanced analytical models to embed this uncertainty in its generation profile. This research focuses on the development of innovative mathematical modeling and analysis tools to improve our understanding of the effects of wind generation on power systems. The overall goal of this research is to introduce novel analytical frameworks to consider the penetration of wind generation sources within the distribution and transmission networks. In particular, two main operational problems are addressed within this thesis; the Distribution Load Flow (DLF) problem and the Unit Commitment (UC) problem in the presence of wind generation. First for the DLF problem, a novel probabilistic wind generation model is presented. The probabilistic wind generation profile, which is a function of the wind speed, is considered and an appropriate procedure is developed to classify specific levels based on wind speed, in order to reduce the number of probabilistic combinations of wind power generation. Next, a novel Probabilistic Distribution Load Flow (PDLF) approach is used to evaluate the impact of wind penetration into distribution systems. The traditional DLF program is modified to include the wind generation profiles. Three Wind Turbine (WT) models are derived and integrated within the PDLF program to examine and compare their performance. The probabilistic forward-backward sweep algorithm is developed for the first two models of WT. For the third model of WT, a probabilistic compensation-based load flow is presented. The effect of WT penetration is investigated on feeder losses, voltage profile and line flows. Secondly, a new scenario generation and reduction technique is developed for analyzing the effects of wind generation uncertainties on short-term power system operation. A historical wind speed data set is used to obtain different wind speed clusters which are then processed through Monte Carlo Simulations (MCS), Markov-chains and a forward selection scenario reduction algorithm to obtain a reduced set of scenarios. These reduced scenarios are then incorporated into a Locational Marginal Price (LMP) based electricity market settlement and dispatch model. These UC type models incorporate system constraints and transmission constraints to examine the effects of wind generation on electricity market prices, UC decisions including generation, reserve requirement, load cleared and social welfare. Markov-chain transition matrices are developed to include the effect of the inter-hour transition correlation of wind speed from one specific hour to the following hour to improve the generation of the wind scenarios. The effect of changing wind farm capacity on system operation is also discussed. Furthermore, the impact of the wake-effect phenomena influencing off-shore wind turbines is explained. Finally, this research examines the effect of wind generation penetration on the environmental emissions. A novel methodology is developed to evaluate the environmental impact of wind generation penetration into electrical power systems. The solution of the market dispatch UC model is studied for different cost functions with an emission cap. The relationship between changing the emission caps and the penetration level of wind energy is investigated. Furthermore, the effect on market prices is also examined when emission caps are imposed by external agencies, on the System Operator (SO).