Matching Items (13)
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Description
Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly

Under the framework of intelligent management of power grids by leveraging advanced information, communication and control technologies, a primary objective of this study is to develop novel data mining and data processing schemes for several critical applications that can enhance the reliability of power systems. Specifically, this study is broadly organized into the following two parts: I) spatio-temporal wind power analysis for wind generation forecast and integration, and II) data mining and information fusion of synchrophasor measurements toward secure power grids. Part I is centered around wind power generation forecast and integration. First, a spatio-temporal analysis approach for short-term wind farm generation forecasting is proposed. Specifically, using extensive measurement data from an actual wind farm, the probability distribution and the level crossing rate of wind farm generation are characterized using tools from graphical learning and time-series analysis. Built on these spatial and temporal characterizations, finite state Markov chain models are developed, and a point forecast of wind farm generation is derived using the Markov chains. Then, multi-timescale scheduling and dispatch with stochastic wind generation and opportunistic demand response is investigated. Part II focuses on incorporating the emerging synchrophasor technology into the security assessment and the post-disturbance fault diagnosis of power systems. First, a data-mining framework is developed for on-line dynamic security assessment by using adaptive ensemble decision tree learning of real-time synchrophasor measurements. Under this framework, novel on-line dynamic security assessment schemes are devised, aiming to handle various factors (including variations of operating conditions, forced system topology change, and loss of critical synchrophasor measurements) that can have significant impact on the performance of conventional data-mining based on-line DSA schemes. Then, in the context of post-disturbance analysis, fault detection and localization of line outage is investigated using a dependency graph approach. It is shown that a dependency graph for voltage phase angles can be built according to the interconnection structure of power system, and line outage events can be detected and localized through networked data fusion of the synchrophasor measurements collected from multiple locations of power grids. Along a more practical avenue, a decentralized networked data fusion scheme is proposed for efficient fault detection and localization.
ContributorsHe, Miao (Author) / Zhang, Junshan (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Hedman, Kory (Committee member) / Si, Jennie (Committee member) / Ye, Jieping (Committee member) / Arizona State University (Publisher)
Created2013
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Description
This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified

This thesis outlines the development of a vector retrieval technique, based on data assimilation, for a coherent Doppler LIDAR (Light Detection and Ranging). A detailed analysis of the Optimal Interpolation (OI) technique for vector retrieval is presented. Through several modifications to the OI technique, it is shown that the modified technique results in significant improvement in velocity retrieval accuracy. These modifications include changes to innovation covariance portioning, covariance binning, and analysis increment calculation. It is observed that the modified technique is able to make retrievals with better accuracy, preserves local information better, and compares well with tower measurements. In order to study the error of representativeness and vector retrieval error, a lidar simulator was constructed. Using the lidar simulator a thorough sensitivity analysis of the lidar measurement process and vector retrieval is carried out. The error of representativeness as a function of scales of motion and sensitivity of vector retrieval to look angle is quantified. Using the modified OI technique, study of nocturnal flow in Owens' Valley, CA was carried out to identify and understand uncharacteristic events on the night of March 27th 2006. Observations from 1030 UTC to 1230 UTC (0230 hr local time to 0430 hr local time) on March 27 2006 are presented. Lidar observations show complex and uncharacteristic flows such as sudden bursts of westerly cross-valley wind mixing with the dominant up-valley wind. Model results from Coupled Ocean/Atmosphere Mesoscale Prediction System (COAMPS®) and other in-situ instrumentations are used to corroborate and complement these observations. The modified OI technique is used to identify uncharacteristic and extreme flow events at a wind development site. Estimates of turbulence and shear from this technique are compared to tower measurements. A formulation for equivalent wind speed in the presence of variations in wind speed and direction, combined with shear is developed and used to determine wind energy content in presence of turbulence.
ContributorsChoukulkar, Aditya (Author) / Calhoun, Ronald (Thesis advisor) / Mahalov, Alex (Committee member) / Kostelich, Eric (Committee member) / Huang, Huei-Ping (Committee member) / Phelan, Patrick (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced

Climate change has been one of the major issues of global economic and social concerns in the past decade. To quantitatively predict global climate change, the Intergovernmental Panel on Climate Change (IPCC) of the United Nations have organized a multi-national effort to use global atmosphere-ocean models to project anthropogenically induced climate changes in the 21st century. The computer simulations performed with those models and archived by the Coupled Model Intercomparison Project - Phase 5 (CMIP5) form the most comprehensive quantitative basis for the prediction of global environmental changes on decadal-to-centennial time scales. While the CMIP5 archives have been widely used for policy making, the inherent biases in the models have not been systematically examined. The main objective of this study is to validate the CMIP5 simulations of the 20th century climate with observations to quantify the biases and uncertainties in state-of-the-art climate models. Specifically, this work focuses on three major features in the atmosphere: the jet streams over the North Pacific and Atlantic Oceans and the low level jet (LLJ) stream over central North America which affects the weather in the United States, and the near-surface wind field over North America which is relevant to energy applications. The errors in the model simulations of those features are systematically quantified and the uncertainties in future predictions are assessed for stakeholders to use in climate applications. Additional atmospheric model simulations are performed to determine the sources of the errors in climate models. The results reject a popular idea that the errors in the sea surface temperature due to an inaccurate ocean circulation contributes to the errors in major atmospheric jet streams.
ContributorsKulkarni, Sujay (Author) / Huang, Huei-Ping (Thesis advisor) / Calhoun, Ronald (Committee member) / Peet, Yulia (Committee member) / Arizona State University (Publisher)
Created2014
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Description
With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was

With a ground-based Doppler lidar on the upwind side of a wind farm in the Tehachapi Pass of California, radial wind velocity measurements were collected for repeating sector sweeps, scanning up to 10 kilometers away. This region consisted of complex terrain, with the scans made between mountains. The dataset was utilized for techniques being studied for short-term forecasting of wind power by correlating changes in energy content and of turbulence intensity by tracking spatial variance, in the wind ahead of a wind farm. A ramp event was also captured and its propagation was tracked.

Orthogonal horizontal wind vectors were retrieved from the radial velocity using a sector Velocity Azimuth Display method. Streamlines were plotted to determine the potential sites for a correlation of upstream wind speed with wind speed at downstream locations near the wind farm. A "virtual wind turbine" was "placed" in locations along the streamline by using the time-series velocity data at the location as the input to a modeled wind turbine, to determine the extractable energy content at that location. The relationship between this time-dependent energy content upstream and near the wind farm was studied. By correlating the energy content with each upstream location based on a time shift estimated according to advection at the mean wind speed, several fits were evaluated. A prediction of the downstream energy content was produced by shifting the power output in time and applying the best-fit function. This method made predictions of the power near the wind farm several minutes in advance. Predictions were also made up to an hour in advance for a large ramp event. The Magnitude Absolute Error and Standard Deviation are presented for the predictions based on each selected upstream location.
ContributorsMagerman, Beth (Author) / Calhoun, Ronald (Thesis advisor) / Peet, Yulia (Committee member) / Huang, Huei-Ping (Committee member) / Krishnamurthy, Raghavendra (Committee member) / Arizona State University (Publisher)
Created2014
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Description
This thesis concerns the impact of energy storage on the power system. The rapidly increasing integration of renewable energy source into the grid is driving greater attention towards electrical energy storage systems which can serve many applications like economically meeting peak loads, providing spinning reserve. Economic dispatch is performed with

This thesis concerns the impact of energy storage on the power system. The rapidly increasing integration of renewable energy source into the grid is driving greater attention towards electrical energy storage systems which can serve many applications like economically meeting peak loads, providing spinning reserve. Economic dispatch is performed with bulk energy storage with wind energy penetration in power systems allocating the generation levels to the units in the mix, so that the system load is served and most economically. The results obtained in previous research to solve for economic dispatch uses a linear cost function for a Direct Current Optimal Power Flow (DCOPF). This thesis uses quadratic cost function for a DCOPF implementing quadratic programming (QP) to minimize the function. A Matlab program was created to simulate different test systems including an equivalent section of the WECC system, namely for Arizo-na, summer peak 2009. A mathematical formulation of a strategy of when to charge or discharge the storage is incorporated in the algorithm. In this thesis various test cases are shown in a small three bus test bed and also for the state of Arizona test bed. The main conclusions drawn from the two test beds is that the use of energy storage minimizes the generation dispatch cost of the system and benefits the power sys-tem by serving the peak partially from stored energy. It is also found that use of energy storage systems may alleviate the loading on transmission lines which can defer the upgrade and expansion of the transmission system.
ContributorsGupta, Samir (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2012
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Description
This thesis is focused on the study of wind energy integration and is divided into two segments. The first part of the thesis deals with developing a reliability evaluation technique for a wind integrated power system. A multiple-partial outage model is utilized to accurately calculate the wind generation availability. A

This thesis is focused on the study of wind energy integration and is divided into two segments. The first part of the thesis deals with developing a reliability evaluation technique for a wind integrated power system. A multiple-partial outage model is utilized to accurately calculate the wind generation availability. A methodology is presented to estimate the outage probability of wind generators while incorporating their reduced power output levels at low wind speeds. Subsequently, power system reliability is assessed by calculating the loss of load probability (LOLP) and the effect of wind integration on the overall system is analyzed. Actual generation and load data of the Texas power system in 2008 are used to construct a test case. To demonstrate the robustness of the method, relia-bility studies have been conducted for a fairly constant as well as for a largely varying wind generation profile. Further, the case of increased wind generation penetration level has been simulated and comments made about the usability of the proposed method to aid in power system planning in scenarios of future expansion of wind energy infrastructure. The second part of this thesis explains the development of a graphic user interface (GUI) to demonstrate the operation of a grid connected doubly fed induction generator (DFIG). The theory of DFIG and its back-to-back power converter is described. The GUI illustrates the power flow, behavior of the electrical circuit and the maximum power point tracking of the machine for a variable wind speed input provided by the user. The tool, although developed on MATLAB software platform, has been constructed to work as a standalone application on Windows operating system based computer and enables even the non-engineering students to access it. Results of both the segments of the thesis are discussed. Remarks are presented about the validity of the reliability technique and GUI interface for variable wind speed conditions. Improvements have been suggested to enable the use of the reliability technique for a more elaborate system. Recommendations have been made about expanding the features of the GUI tool and to use it to promote educational interest about renewable power engineering.
ContributorsSinha, Anubhav (Author) / Heydt, Gerald T (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Ayyanar, Raja (Committee member) / Karady, George G. (Committee member) / Arizona State University (Publisher)
Created2012
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Description
Development of renewable energy solutions has become a major interest among environmental organizations and governments around the world due to an increase in energy consumption and global warming. One fast growing renewable energy solution is the application of wind energy in cities. To qualitative and quantitative predict wind turbine performance

Development of renewable energy solutions has become a major interest among environmental organizations and governments around the world due to an increase in energy consumption and global warming. One fast growing renewable energy solution is the application of wind energy in cities. To qualitative and quantitative predict wind turbine performance in urban areas, CFD simulation is performed on real-life urban geometry and wind velocity profiles are evaluated. Two geometries in Arizona is selected in this thesis to demonstrate the influence of building heights; one of the simulation models, ASU campus, is relatively low rise and without significant tall buildings; the other model, the downtown phoenix model, are high-rise and with greater building height difference. The content of this thesis focuses on using RANS computational fluid dynamics approach to simulate wind acceleration phenomenon in two complex geometries, ASU campus and Phoenix downtown model. Additionally, acceleration ratio and locations are predicted, the results are then used to calculate the best location for small wind turbine installments.
ContributorsYing, Xiaoyan (Author) / Huang, Huei-Ping (Thesis advisor) / Peet, Yulia (Committee member) / Herrmann, Marcus (Committee member) / Arizona State University (Publisher)
Created2015
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Description
For the increasing concerns of influence on environment by fossil-electricity generation, application of renewable energy becomes one of the most focused issues in society. Based on the limitation on urban environment, wind turbines, which can be mounted on rooftop or between buildings, are regarded as a feasible way for wind

For the increasing concerns of influence on environment by fossil-electricity generation, application of renewable energy becomes one of the most focused issues in society. Based on the limitation on urban environment, wind turbines, which can be mounted on rooftop or between buildings, are regarded as a feasible way for wind energy generation. This study presents wind flow simulations in a large-scale environment with certain dimension buildings. Different inlet velocity boundary conditions are tested firstly, and the non-uniform inlet boundary condition shows better agreement with realistic situation. Turbulence intensity is set to be 10% for comparison consistency. The k-epsilon turbulence model is regarded as a better simulation for this certain condition. After that, three different structures, which include single building, pristine double building and modified circular gap double building systems, are tested in this environment condition. The result shows 18.8% velocity increasing on the top of single building system. Pristine double building systems are tested with 4 different gap distances, and building with 10 meters gap achieved the best velocity condition, which 32.8% velocity increasing and 11.8% improvement comparing to single building system, respectively. But the location of maximum velocity moves to the gap and the maximum velocity on the rooftop of double building system is approximately 5.1% lower than single building system. Based on previous study, modified circular gap double building system is created with 10 meters gap. Comparing result with single building system, modified circular gap system achieves higher improvement for wind flow, whose improvement of velocity increasing in the gap and on the rooftop of building are 47.1% and 3.0%, respectively. As a result, the modified circular gap double building can be regarded as a high efficiency system of environmental wind flow over buildings for renewable energy system.
ContributorsLi, Guoyi (Author) / Huang, Huei-Ping (Thesis advisor) / Lee, Taewoo (Committee member) / Forzani, Erica (Committee member) / Arizona State University (Publisher)
Created2015
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Description
As the world embraces a sustainable energy future, alternative energy resources, such as wind power, are increasingly being seen as an integral part of the future electric energy grid. Ultimately, integrating such a dynamic and variable mix of generation requires a better understanding of renewable generation output, in addition to

As the world embraces a sustainable energy future, alternative energy resources, such as wind power, are increasingly being seen as an integral part of the future electric energy grid. Ultimately, integrating such a dynamic and variable mix of generation requires a better understanding of renewable generation output, in addition to power grid systems that improve power system operational performance in the presence of anticipated events such as wind power ramps. Because of the stochastic, uncontrollable nature of renewable resources, a thorough and accurate characterization of wind activity is necessary to maintain grid stability and reliability. Wind power ramps from an existing wind farm are studied to characterize persistence forecasting errors using extreme value analysis techniques. In addition, a novel metric that quantifies the amount of non-stationarity in time series wind power data was proposed and used in a real-time algorithm to provide a rigorous method that adaptively determines training data for forecasts. Lastly, large swings in generation or load can cause system frequency and tie-line flows to deviate from nominal, so an anticipatory MPC-based secondary control scheme was designed and integrated into an automatic generation control loop to improve the ability of an interconnection to respond to anticipated large events and fluctuations in the power system.
ContributorsGanger, David (Author) / Vittal, Vijay (Thesis advisor) / Zhang, Junshan (Thesis advisor) / Hedman, Kory (Committee member) / Undrill, John (Committee member) / Arizona State University (Publisher)
Created2016
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Description
Large-scale integration of wind generation introduces planning and operational difficulties due to the intermittent and highly variable nature of wind. In particular, the generation from non-hydro renewable resources is inherently variable and often times difficult to predict. Integrating significant amounts of renewable generation, thus, presents a challenge to the power

Large-scale integration of wind generation introduces planning and operational difficulties due to the intermittent and highly variable nature of wind. In particular, the generation from non-hydro renewable resources is inherently variable and often times difficult to predict. Integrating significant amounts of renewable generation, thus, presents a challenge to the power systems operators, requiring additional flexibility, which may incur a decrease of conventional generation capacity.

This research investigates the algorithms employing emerging computational advances in system operation policies that can improve the flexibility of the electricity industry. The focus of this study is on flexible operation policies for renewable generation, particularly wind generation. Specifically, distributional forecasts of windfarm generation are used to dispatch a “discounted” amount of the wind generation, leaving a reserve margin that can be used for reserve if needed. This study presents systematic mathematic formulations that allow the operator incorporate this flexibility into the operation optimization model to increase the benefits in the energy and reserve scheduling procedure. Incorporating this formulation into the dispatch optimization problem provides the operator with the ability of using forecasted probability distributions as well as the off-line generated policies to choose proper approaches for operating the system in real-time. Methods to generate such policies are discussed and a forecast-based approach for developing wind margin policies is presented. The impacts of incorporating such policies in the electricity market models are also investigated.
ContributorsHedayati Mehdiabadi, Mojgan (Author) / Zhang, Junshan (Thesis advisor) / Hedman, Kory (Thesis advisor) / Heydt, Gerald (Committee member) / Tepedelenlioğlu, Cihan (Committee member) / Arizona State University (Publisher)
Created2017