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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).

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).

One of the great challenges to increasing the use of wind generation is the need to ensure generation adequacy. In this dissertation, we address that need by investigating and assessing the planning and operational generation adequacy of power systems with significant wind generation. At the onset of this dissertation, key metrics are presented for determining a power system’s generation adequacy assessment based on loss-of-load analytical methods. With these key metrics understood, a detailed methodology is put forward on how to integrate wind plants in the assessment’s framework. Then, through the examination of a case study, we demonstrate that wind generation does contribute capacity to the system generation adequacy. Indeed, results indicates that at wind penetration levels of less than 5%, a wind plant’s reliability impact is comparable to an energy equivalent conventional unit. We then show how to quantify a wind plant’s capacity contribution by using the effective load carrying capability metric (ELCC), providing a detailed description of how to implement this metric in the context of wind generation. However, as certain computational setbacks are inherent to the metric, a novel noniterative approximation is proposed and applied to various case studies. The accuracy of the proposed approximation is evaluated in a comparative study by contrasting the resulting estimates to conventionally-computed ELCC values and the wind plant’s capacity factor. The non-iterative method is shown to yield accurate ELCC estimates with relative errors averaging around 2%. Case study findings also suggest the importance of period-specific ELCC calculations to better evaluate the variable capacity contribution of wind plants. Even when considering a well-planned system in which wind generation has been appropriately integrated in the adequacy assessment, wind plants do create significant challenges in maintaining generation adequacy on an operational level. To address these challenges, a novel operational reliability assessment tool is proposed to quantitatively evaluate the system’s operational generation adequacy given potential generator forced outages, load and wind power forecasts, and forecasting deviations. / text

In recent decades, there has been a dramatic increase in utilizing renewable energy resources by many power utilities around the world. The tendency toward using renewable energy resources is mainly due to the environmental concerns and fuel cost escalation associated with conventional fossil generation. Among renewable resources, wind energy is a proven source for power generation that positively contributes to global, social, and economic environments. Nowadays, wind energy is a mature, abundant, and emission-free power generation technology, and a significant percentage of electrical power demand is supplied by wind. However, the intermittent nature of wind generation introduces various challenges for both the operation and planning of power systems. One of the problems of increasing the use of wind generation can be seen from the reliability assessment point of view. Indeed, there is a recognized need to study the contribution of wind generation to overall system reliability and to ensure the adequacy of generation capacity. Wind power generation is different than conventional generation (i.e., fossil-based) in that wind power is variable and non-controllable, which can affect power system reliability. Therefore, modeling wind generation in a reliability assessment calls for reliable stochastic simulation techniques that can properly handle the uncertainty and precisely reflect the variable characteristics of the wind at a particular site. The research presented in this thesis focuses on developing a reliable and appropriate model for the reliability assessment of power system generation, including wind energy sources. This thesis uses the Monte Carlo Markov Chain (MCMC) technique due to its ability to produce synthetic wind power time series data that sufficiently consider the randomness of the wind along with keeping the statistical and temporal characteristics of the measured data. Thereafter, the synthetic wind power time series based on MCMC is coupled with a probabilistic sequential methodology for conventional generation in order to assess the overall adequacy of generating systems. The study presented in this thesis is applied to two test systems, designated the Roy Billinton Test System (RBTS) and the IEEE Reliability Test System (IEEE-RTS). A wide range of reliability indices are then calculated, including loss of load expectation (LOLE), loss of energy expectation (LOEE), loss of load frequency (LOLF), energy not supplied per interruption (ENSPI), demand not supplied per interruption (DNSPI), and expected duration per interruption (EDPI). To show the effectiveness of the proposed methodology, a further study is conducted to compare the obtained reliability indices using the MCMC model and the ARMA model, which is often used in reliability studies. The methodologies and the results illustrated in this thesis aim to provide useful information to planners or developers who endeavor to assess the reliability of power generation systems that contain wind generation.

Master of Science / Department of Electrical and Computer Engineering / Anil Pahwa / With the Smart Grid trend setting in, various techniques to make the existing grid smarter are being considered. The price of electricity is one of the major factors, which affects the electric utility as well as the numerous consumers connected to the grid. Therefore deciding the right price of electricity for the time of day would be an important decision to make. Consumers’ response to this change in price will impact peak demand as well as their own annual energy bill. Owning a small wind generator under the Critical Peak Pricing (CPP) and Time of Use (TOU) price-based demand response programs could be a viable option. Economic evaluation of owning a small wind generator under the two pricing schemes, namely Critical Peak Pricing (CPP) and Time of Use (TOU), is the main focus of this research. Analysis shows that adopting either of the pricing schemes will not change the annual energy bill for the consumer. Taking into account the installed cost of the turbine, it may not be significantly economical for a residential homeowner to own a small wind turbine with either of the pricing schemes in effect under the conditions assumed.

As the technology behind renewable energy sources becomes more advanced and cost-effective, these sources have become an ever-increasing portion of the generation portfolios of power systems across the country. While the shift away from non-renewable resources is generally considered beneficial, the fact remains that intermittent renewable sources present special challenges associated with their unique operating characteristics. Because of the high variability of intermittent renewables, the frequency performance of the system to which they are connected can degrade. Generators assigned to regulate frequency, keeping it close to the desired 60 Hz, are forced to ramp up and down quickly in order to offset the rise and fall of the variable resources (in addition to the rise and fall of load), causing transient frequency deviations, power swings, major interface transfer variations and other significant issues. This research measures the impact of intermittent renewable resource penetration level on power system frequency performance, and offers methods for managing that performance. Currently, the generally accepted amount of regulation (rapidly-dispatchable reserve, used as a supplement to base generation on a short time scale to avoid performance issues) is 1% of peak load. Because of the high variability associated with intermittent renewables, including wind generation (the focus of this thesis), it is expected that this amount of regulation must increase in order to maintain adequate system frequency performance. Thus, the primary objective of this thesis is to quantify the amount of regulation necessary to maintain adequate frequency performance as a function of the penetration level of wind generation. Presently, balancing resource requirements are computed, in both industry and in the research literature, using static models, which rely entirely on statistical manipulation of net load, failing to capture the intricacies of dynamic system and generator interactions. Using a dynamic model with high temporal resolution data, instead of these statistical models, this thesis confirms the need for additional regulation as wind generation penetration increases. But beyond that, our research demonstrates an exponentially increasing relationship between necessary regulation and wind generation percentage, indicating that, without further technological breakthroughs, there is a practical limit to the amount of wind generation that a typical system can accommodate. Furthermore, we compare our dynamic model results with those of the statistical models, and show that the majority of current statistical models substantially under-predict the necessary amount of regulation to accommodate significant amounts of wind generation. Finally, we verify that the ramping capability of the regulating generators impacts the amount of necessary regulation, although it is generally ignored in current analysis and related literature.

[pt] Um dos principais problemas para a expansão do uso da energia eólica é a escassez de dados. No Brasil, exige-se um histórico de pelo menos 30 anos de produção para a certificação de um parque eólico. No entanto, é muito improvável que esses dados estejam disponíveis. Um recurso frequente é o de utilizar um histórico de medidas locais com uma duração bastante inferior (por exemplo 2 anos) e estendê-lo para 30 anos através do uso de modelos estatísticos. O objetivo dessa dissertação é propor e estudar o desempenho de uma metodologia de extensão de histórico baseada em um modelo de regressão linear. Como ilustração, a metodologia foi aplicada a 4 parques eólicos localizados no nordeste do Brasil. / [en] One of the main problems for the expansion for the use of wind energy is the lack of data. In Brazil, it is required a historic data of at least 30 years of production for the certification of a wind farm. However, is very unlikely that these data is available. A frequent use is to use historic data of local measurements with a short duration (2 years for example) e extend for 30 years through the use of statistical models. The objective of this dissertation is to propose e study the performance of a methodology for the historic data extension based on a linear regression model. As an illustration, the methodology was applied to 4 wind farms located on the northeast of Brazil.

This thesis deals with the performance of a Wind Energy Conversion System operating as a power generator and Active Filter simultaneously. As a power generator, the Wind Energy Conversion System converts wind energy into electric energy; as an Active Filter, it sinks the harmonic currents injected by Non-Linear Loads connected at the same feeder. Three control systems are developed to ensure the described operation; a specific study regarding the compensation of the triplen harmonics is carried out; Doubly-Fed Induction Generator derating is defined; and an engineering economic analysis is performed to determine the profitability of the proposed operation. The Wind Energy Conversion System performance as generator and Active Filter has been studied for steady-state analysis, fast transients and low transients. It is concluded that the proposed control systems allow operating the Wind Energy Conversion System as power generator and harmonic compensator both during steady state and transient operation; the described operation causes power loss increase and voltage distortion that determine the choice of the component and require system derating.

In this dissertation, a high-frequency (HF) transformer isolated grid-connected power converter system with battery backup function is proposed for a small-scale wind generation system (less than 100 kW) using permanent magnet synchronous generator (PMSG). The system includes a main HF isolated DC/AC grid-connected converter and a bidirectional HF isolated DC/DC converter. Through literature survey and some comparative studies, a HF isolated DC/DC converter followed by a line connected inverter (LCI) is chosen as the grid-connected scheme. After reviewing several topologies which were used in such a DC/AC converter with an unfolding stage, a DC/AC grid-connected converter based on dual- bridge LCL-type resonant topology is proposed. Through the control of the phase- shift angle between the two bridges, a rectified sinusoidal dc link current can be modulated, which in turn can be unfolded by the LCI. This converter is analyzed with Fourier series analysis approach. It is shown that all switches in both bridges can work in zero-voltage switching (ZVS) at any phase-shift and load conditions. The redundancy of the dual-bridge structure make it easy to accommodate higher power flow. A design example of a 500 W converter is given and simulated. A prototype is built and tested in the lab to validate its performance. The simulation and experimental results show a reasonable match to the theoretical analysis. The expansion to three-phase grid-connection is discussed with phase-shifted parallel operation of three identical units. Input and output current harmonics of different arrangements are analyzed to search for the best choice. As the feature of a hybrid wind generation application, the battery backup function is fulfilled with a bidirectional HF transformer isolated DC/DC converter. This dual-bridge series resonant converter (DBSRC) is analyzed with two ac equivalent circuit approaches for resistive load and battery load respectively, which give same results. Soft-switching is achieved for all switches on both sides of the HF transformer. Test plots obtained from simulation and experiment are included for validation.