Matching Items (87)
Description
The main objective of this research is to develop an integrated method to study emergent behavior and consequences of evolution and adaptation in engineered complex adaptive systems (ECASs). A multi-layer conceptual framework and modeling approach including behavioral and structural aspects is provided to describe the structure of a class of engineered complex systems and predict their future adaptive patterns. The approach allows the examination of complexity in the structure and the behavior of components as a result of their connections and in relation to their environment. This research describes and uses the major differences of natural complex adaptive systems (CASs) with artificial/engineered CASs to build a framework and platform for ECAS. While this framework focuses on the critical factors of an engineered system, it also enables one to synthetically employ engineering and mathematical models to analyze and measure complexity in such systems. In this way concepts of complex systems science are adapted to management science and system of systems engineering. In particular an integrated consumer-based optimization and agent-based modeling (ABM) platform is presented that enables managers to predict and partially control patterns of behaviors in ECASs. Demonstrated on the U.S. electricity markets, ABM is integrated with normative and subjective decision behavior recommended by the U.S. Department of Energy (DOE) and Federal Energy Regulatory Commission (FERC). The approach integrates social networks, social science, complexity theory, and diffusion theory. Furthermore, it has unique and significant contribution in exploring and representing concrete managerial insights for ECASs and offering new optimized actions and modeling paradigms in agent-based simulation.
ContributorsHaghnevis, Moeed (Author) / Askin, Ronald G. (Thesis advisor) / Armbruster, Dieter (Thesis advisor) / Mirchandani, Pitu (Committee member) / Wu, Tong (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
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 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
Description
With the rapid growth of power systems and the concomitant technological advancements, the goal of achieving smart grids is no longer a vision but a foreseeable reality. Hence, the existing grids are undergoing infrastructural modifications to achieve the diverse characteristics of a smart grid. While there are many subjects associated with the operation of smart grids, this dissertation addresses two important aspects of smart grids: increased penetration of renewable resources, and increased reliance on sensor systems to improve reliability and performance of critical power system components. Present renewable portfolio standards are changing both structural and performance characteristics of power systems by replacing conventional generation with alternate energy resources such as photovoltaic (PV) systems. The present study investigates the impact of increased penetration of PV systems on steady state performance as well as transient stability of a large power system which is a portion of the Western U.S. interconnection. Utility scale and residential rooftop PVs are added to replace a portion of conventional generation resources. While steady state voltages are observed under various PV penetration levels, the impact of reduced inertia on transient stability performance is also examined. The simulation results obtained effectively identify both detrimental and beneficial impacts of increased PV penetration both for steady state stability and transient stability performance. With increased penetration of the renewable energy resources, and with the current loading scenario, more transmission system components such as transformers and circuit breakers are subject to increased stress and overloading. This research work explores the feasibility of increasing system reliability by applying condition monitoring systems to selected circuit breakers and transformers. A very important feature of smart grid technology is that this philosophy decreases maintenance costs by deploying condition monitoring systems that inform the operator of impending failures; or the approach can ameliorate problematic conditions. A method to identify the most critical transformers and circuit breakers with the aid of contingency ranking methods is presented in this study. The work reported in this dissertation parallels an industry sponsored study in which a considerable level of industry input and industry reported concerns are reflected.
ContributorsEftekharnejad, Sara (Author) / Heydt, Gerald (Thesis advisor) / Vittal, Vijay (Thesis advisor) / Si, Jennie (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2012
Description
Battery energy storage has shown a lot of potential in the recent past to be effective in various grid services due to its near instantaneous ramp rates and modularity. This thesis aims to determine the commercial viability of customer premises and substation sited battery energy storage systems. Five different types of services have been analyzed considering current market pricing of Lithium-ion batteries and power conditioning equipment. Energy Storage Valuation Tool 3.0 (Beta) has been used to exclusively determine the value of energy storage in the services analyzed. The results indicate that on the residential level, Lithium-ion battery energy storage may not be a cost beneficial option for retail tariff management or demand charge management as only 20-30% of the initial investment is recovered at the end of 15 year plant life. SRP's two retail Time-of-Use price plans E-21 and E-26 were analyzed in respect of their ability to increase returns from storage compared to those with flat pricing. It was observed that without a coupled PV component, E-21 was more suitable for customer premises energy storage, however, its revenue stream reduces with addition to PV. On the grid scale, however, with carefully chosen service hierarchy such as distribution investment deferral, spinning or balancing reserve support, the initial investment can be recovered to an extent of about 50-70%. The study done here is specific to Salt River Project inputs and data. Results for all the services analyzed are highly location specific and are only indicative of the overall viability and returns from them.
ContributorsNadkarni, Aditya (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation presents a new hybrid fault current limiter (FCL) topology that is primarily intended to protect single-phase power equipment. It can however be extended to protect three phase systems but would need three devices to protect each individual phase. In comparison against the existing fault current limiter technology, the salient fea-tures of the proposed topology are: a) provides variable impedance that provides a 50% reduction in prospective fault current; b) near instantaneous response time which is with-in the first half cycle (1-4 ms); c) the use of semiconductor switches as the commutating switch which produces reduced leakage current, reduced losses, improved reliability, and a faster switch time (ns-µs); d) zero losses in steady-state operation; e) use of a Neodym-ium (NdFeB) permanent magnet as the limiting impedance which reduces size, cost, weight, eliminates DC biasing and cooling costs; f) use of Pulse Width Modulation (PWM) to control the magnitude of the fault current to a user's desired level. g) experi-mental test system is developed and tested to prove the concepts of the proposed FCL. This dissertation presents the proposed topology and its working principle backed up with numerical verifications, simulation results, and hardware implementation results. Conclu-sions and future work are also presented.
ContributorsPrigmore, Jay (Author) / Karady, George G. (Thesis advisor) / Ayyanar, Raja (Committee member) / Holbert, Keith E. (Committee member) / Hedman, Kory (Committee member) / Arizona State University (Publisher)
Created2013
Description
The combined heat and power (CHP)-based distributed generation (DG) or dis-tributed energy resources (DERs) are mature options available in the present energy mar-ket, considered to be an effective solution to promote energy efficiency. In the urban en-vironment, the electricity, water and natural gas distribution networks are becoming in-creasingly interconnected with the growing penetration of the CHP-based DG. Subse-quently, this emerging interdependence leads to new topics meriting serious consideration: how much of the CHP-based DG can be accommodated and where to locate these DERs, and given preexisting constraints, how to quantify the mutual impacts on operation performances between these urban energy distribution networks and the CHP-based DG. The early research work was conducted to investigate the feasibility and design methods for one residential microgrid system based on existing electricity, water and gas infrastructures of a residential community, mainly focusing on the economic planning. However, this proposed design method cannot determine the optimal DG sizing and sit-ing for a larger test bed with the given information of energy infrastructures. In this con-text, a more systematic as well as generalized approach should be developed to solve these problems. In the later study, the model architecture that integrates urban electricity, water and gas distribution networks, and the CHP-based DG system was developed. The pro-posed approach addressed the challenge of identifying the optimal sizing and siting of the CHP-based DG on these urban energy networks and the mutual impacts on operation per-formances were also quantified. For this study, the overall objective is to maximize the electrical output and recovered thermal output of the CHP-based DG units. The electrici-ty, gas, and water system models were developed individually and coupled by the devel-oped CHP-based DG system model. The resultant integrated system model is used to constrain the DG's electrical output and recovered thermal output, which are affected by multiple factors and thus analyzed in different case studies. The results indicate that the designed typical gas system is capable of supplying sufficient natural gas for the DG normal operation, while the present water system cannot support the complete recovery of the exhaust heat from the DG units.
ContributorsZhang, Xianjun (Author) / Karady, George G. (Thesis advisor) / Ariaratnam, Samuel T. (Committee member) / Holbert, Keith E. (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
This dissertation considers an integrated approach to system design and controller design based on analyzing limits of system performance. Historically, plant design methodologies have not incorporated control relevant considerations. Such an approach could result in a system that might not meet its specifications (or one that requires a complex control architecture to do so). System and controller designers often go through several iterations in order to converge to an acceptable plant and controller design. The focus of this dissertation is on the design and control an air-breathing hypersonic vehicle using such an integrated system-control design framework. The goal is to reduce the number of system-control design iterations (by explicitly incorporate control considerations in the system design process), as well as to influence the guidance/trajectory specifications for the system. Due to the high computational costs associated with obtaining a dynamic model for each plant configuration considered, approximations to the system dynamics are used in the control design process. By formulating the control design problem using bilinear and polynomial matrix inequalities, several common control and system design constraints can be simultaneously incorporated into a vehicle design optimization. Several design problems are examined to illustrate the effectiveness of this approach (and to compare the computational burden of this methodology against more traditional approaches).
ContributorsSridharan, Srikanth (Author) / Rodriguez, Armando A (Thesis advisor) / Mittelmann, Hans D (Committee member) / Si, Jennie (Committee member) / Tsakalis, Konstantinos S (Committee member) / Arizona State University (Publisher)
Created2014
Description
The basal ganglia are four sub-cortical nuclei associated with motor control and reward learning. They are part of numerous larger mostly segregated loops where the basal ganglia receive inputs from specific regions of cortex. Converging on these inputs are dopaminergic neurons that alter their firing based on received and/or predicted rewarding outcomes of a behavior. The basal ganglia's output feeds through the thalamus back to the areas of the cortex where the loop originated. Understanding the dynamic interactions between the various parts of these loops is critical to understanding the basal ganglia's role in motor control and reward based learning. This work developed several experimental techniques that can be applied to further study basal ganglia function. The first technique used micro-volume injections of low concentration muscimol to decrease the firing rates of recorded neurons in a limited area of cortex in rats. Afterwards, an artificial cerebrospinal fluid flush was injected to rapidly eliminate the muscimol's effects. This technique was able to contain the effects of muscimol to approximately a 1 mm radius volume and limited the duration of the drug effect to less than one hour. This technique could be used to temporarily perturb a small portion of the loops involving the basal ganglia and then observe how these effects propagate in other connected regions. The second part applied self-organizing maps (SOM) to find temporal patterns in neural firing rate that are independent of behavior. The distribution of detected patterns frequency on these maps can then be used to determine if changes in neural activity are occurring over time. The final technique focused on the role of the basal ganglia in reward learning. A new conditioning technique was created to increase the occurrence of selected patterns of neural activity without utilizing any external reward or behavior. A pattern of neural activity in the cortex of rats was selected using an SOM. The pattern was then reinforced by being paired with electrical stimulation of the medial forebrain bundle triggering dopamine release in the basal ganglia. Ultimately, this technique proved unsuccessful possibly due to poor selection of the patterns being reinforced.
ContributorsBaldwin, Nathan Aaron (Author) / Helms Tillery, Stephen I (Thesis advisor) / Castaneda, Edward (Committee member) / Buneo, Christopher A (Committee member) / Muthuswamy, Jitendran (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014
Description
This study focuses on state estimation of nonlinear discrete time systems with constraints. Physical processes have inherent in them, constraints on inputs, outputs, states and disturbances. These constraints can provide additional information to the estimator in estimating states from the measured output. Recursive filters such as Kalman Filters or Extended Kalman Filters are commonly used in state estimation; however, they do not allow inclusion of constraints in their formulation. On the other hand, computational complexity of full information estimation (using all measurements) grows with iteration and becomes intractable. One way of formulating the recursive state estimation problem with constraints is the Moving Horizon Estimation (MHE) approximation. Estimates of states are calculated from the solution of a constrained optimization problem of fixed size. Detailed formulation of this strategy is studied and properties of this estimation algorithm are discussed in this work. The problem with the MHE formulation is solving an optimization problem in each iteration which is computationally intensive. State estimation with constraints can be formulated as Extended Kalman Filter (EKF) with a projection applied to estimates. The states are estimated from the measurements using standard Extended Kalman Filter (EKF) algorithm and the estimated states are projected on to a constrained set. Detailed formulation of this estimation strategy is studied and the properties associated with this algorithm are discussed. Both these state estimation strategies (MHE and EKF with projection) are tested with examples from the literature. The average estimation time and the sum of square estimation error are used to compare performance of these estimators. Results of the case studies are analyzed and trade-offs are discussed.
ContributorsJoshi, Rakesh (Author) / Tsakalis, Konstantinos (Thesis advisor) / Rodriguez, Armando (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2013
Description
This thesis presents approaches to develop micro seismometers and accelerometers based on molecular electronic transducers (MET) technology using MicroElectroMechanical Systems (MEMS) techniques. MET is a technology applied in seismic instrumentation that proves highly beneficial to planetary seismology. It consists of an electrochemical cell that senses the movement of liquid electrolyte between electrodes by converting it to the output current. MET seismometers have advantages of high sensitivity, low noise floor, small size, absence of fragile mechanical moving parts and independence on the direction of sensitivity axis. By using MEMS techniques, a micro MET seismometer is developed with inter-electrode spacing close to 1μm, which improves the sensitivity of fabricated device to above 3000 V/(m/s^2) under operating bias of 600 mV and input acceleration of 400 μG (G=9.81m/s^2) at 0.32 Hz. The lowered hydrodynamic resistance by increasing the number of channels improves the self-noise to -127 dB equivalent to 44 nG/√Hz at 1 Hz. An alternative approach to build the sensing element of MEMS MET seismometer using SOI process is also presented in this thesis. The significantly increased number of channels is expected to improve the noise performance. Inspired by the advantages of combining MET and MEMS technologies on the development of seismometer, a low frequency accelerometer utilizing MET technology with post-CMOS-compatible fabrication processes is developed. In the fabricated accelerometer, the complicated fabrication of mass-spring system in solid-state MEMS accelerometer is replaced with a much simpler post-CMOS-compatible process containing only deposition of a four-electrode MET structure on a planar substrate, and a liquid inertia mass of an electrolyte droplet encapsulated by oil film. The fabrication process does not involve focused ion beam milling which is used in the micro MET seismometer fabrication, thus the cost is lowered. Furthermore, the planar structure and the novel idea of using an oil film as the sealing diaphragm eliminate the complicated three-dimensional packaging of the seismometer. The fabricated device achieves 10.8 V/G sensitivity at 20 Hz with nearly flat response over the frequency range from 1 Hz to 50 Hz, and a low noise floor of 75 μG/√Hz at 20 Hz.
ContributorsHuang, Hai (Author) / Yu, Hongyu (Thesis advisor) / Jiang, Hanqing (Committee member) / Dai, Lenore (Committee member) / Si, Jennie (Committee member) / Arizona State University (Publisher)
Created2014