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Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating

Traditional approaches to modeling microgrids include the behavior of each inverter operating in a particular network configuration and at a particular operating point. Such models quickly become computationally intensive for large systems. Similarly, traditional approaches to control do not use advanced methodologies and suffer from poor performance and limited operating range. In this document a linear model is derived for an inverter connected to the Thevenin equivalent of a microgrid. This model is then compared to a nonlinear simulation model and analyzed using the open and closed loop systems in both the time and frequency domains. The modeling error is quantified with emphasis on its use for controller design purposes. Control design examples are given using a Glover McFarlane controller, gain sched- uled Glover McFarlane controller, and bumpless transfer controller which are compared to the standard droop control approach. These examples serve as a guide to illustrate the use of multi-variable modeling techniques in the context of robust controller design and show that gain scheduled MIMO control techniques can extend the operating range of a microgrid. A hardware implementation is used to compare constant gain droop controllers with Glover McFarlane controllers and shows a clear advantage of the Glover McFarlane approach.
ContributorsSteenis, Joel (Author) / Ayyanar, Raja (Thesis advisor) / Mittelmann, Hans (Committee member) / Tsakalis, Konstantinos (Committee member) / Tylavsky, Daniel (Committee member) / Arizona State University (Publisher)
Created2013
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Description
Modern measurement schemes for linear dynamical systems are typically designed so that different sensors can be scheduled to be used at each time step. To determine which sensors to use, various metrics have been suggested. One possible such metric is the observability of the system. Observability is a binary condition

Modern measurement schemes for linear dynamical systems are typically designed so that different sensors can be scheduled to be used at each time step. To determine which sensors to use, various metrics have been suggested. One possible such metric is the observability of the system. Observability is a binary condition determining whether a finite number of measurements suffice to recover the initial state. However to employ observability for sensor scheduling, the binary definition needs to be expanded so that one can measure how observable a system is with a particular measurement scheme, i.e. one needs a metric of observability. Most methods utilizing an observability metric are about sensor selection and not for sensor scheduling. In this dissertation we present a new approach to utilize the observability for sensor scheduling by employing the condition number of the observability matrix as the metric and using column subset selection to create an algorithm to choose which sensors to use at each time step. To this end we use a rank revealing QR factorization algorithm to select sensors. Several numerical experiments are used to demonstrate the performance of the proposed scheme.
ContributorsIlkturk, Utku (Author) / Gelb, Anne (Thesis advisor) / Platte, Rodrigo (Thesis advisor) / Cochran, Douglas (Committee member) / Renaut, Rosemary (Committee member) / Armbruster, Dieter (Committee member) / Arizona State University (Publisher)
Created2015
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Description
The Kuramoto model is an archetypal model for studying synchronization in groups

of nonidentical oscillators where oscillators are imbued with their own frequency and

coupled with other oscillators though a network of interactions. As the coupling

strength increases, there is a bifurcation to complete synchronization where all oscillators

move with the same frequency and

The Kuramoto model is an archetypal model for studying synchronization in groups

of nonidentical oscillators where oscillators are imbued with their own frequency and

coupled with other oscillators though a network of interactions. As the coupling

strength increases, there is a bifurcation to complete synchronization where all oscillators

move with the same frequency and show a collective rhythm. Kuramoto-like

dynamics are considered a relevant model for instabilities of the AC-power grid which

operates in synchrony under standard conditions but exhibits, in a state of failure,

segmentation of the grid into desynchronized clusters.

In this dissertation the minimum coupling strength required to ensure total frequency

synchronization in a Kuramoto system, called the critical coupling, is investigated.

For coupling strength below the critical coupling, clusters of oscillators form

where oscillators within a cluster are on average oscillating with the same long-term

frequency. A unified order parameter based approach is developed to create approximations

of the critical coupling. Some of the new approximations provide strict lower

bounds for the critical coupling. In addition, these approximations allow for predictions

of the partially synchronized clusters that emerge in the bifurcation from the

synchronized state.

Merging the order parameter approach with graph theoretical concepts leads to a

characterization of this bifurcation as a weighted graph partitioning problem on an

arbitrary networks which then leads to an optimization problem that can efficiently

estimate the partially synchronized clusters. Numerical experiments on random Kuramoto

systems show the high accuracy of these methods. An interpretation of the

methods in the context of power systems is provided.
ContributorsGilg, Brady (Author) / Armbruster, Dieter (Thesis advisor) / Mittelmann, Hans (Committee member) / Scaglione, Anna (Committee member) / Strogatz, Steven (Committee member) / Welfert, Bruno (Committee member) / Arizona State University (Publisher)
Created2018
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Description
Until late 1970’s the primary focus in power system modeling has been largely directed towards power system generation and transmission. Over the years, the importance of load modeling grew and having an accurate representation of load played an important role in the planning and operation studies. With an emphasis on

Until late 1970’s the primary focus in power system modeling has been largely directed towards power system generation and transmission. Over the years, the importance of load modeling grew and having an accurate representation of load played an important role in the planning and operation studies. With an emphasis on tackling the topic of load modeling, this thesis presents the following intermediary steps in developing accurate load models:

1. Synthesis of a three-phase standard feeder and load model using the measured voltages and currents, for events such as faults and feeder pickup cases, obtained at the head of the feeder.

2. Investigated the impact of the synthesized standard feeder and load model on the sub-transmission system for a feeder pick-up case.

In the first phase of this project, a standard feeder and load model had been synthesized by capturing the current transients when three-phase voltage measurements (obtained from a local electric utility) are played-in as input to the synthesized model. The comparison between the measured currents and the simulated currents obtained using an electromagnetic transient analysis software (PSCAD) are made at the head of the designed feeder. The synthesized load model has a load composition which includes impedance loads, single-phase induction motor loads and three-phase induction motor loads. The parameters of the motor models are adjusted to obtain a good correspondence between measured three-phase currents and simulated current responses at the head of the feeder when subjected to events under which measurements were obtained on the feeder. These events include faults which occurred upstream of the feeder at a higher voltage level and a feeder pickup event that occurred downstream from the head of the feeder. Two different load compositions have been obtained for this feeder and load model depending on the types of load present in the surrounding area (residential or industrial/commercial).

The second phase of this project examines the impact of the feeder pick-up event on the 69 kV sub-transmission system using the obtained standard feeder and load model. Using the 69 kV network data obtained from a local utility, a sub-transmission network has been built in PSCAD. The main difference between the first and second phase of this project is that no measurements are played-in to the model in the latter case. Instead, the feeder pick-up event at a particular substation is simulated using the reduced equivalent of the 69 kV sub-transmission circuit together with the synthesized three-phase models of the feeder and the loads obtained in the first phase of the project. Using this analysis, it is observed that a good correspondence between the PSCAD simulated values of both three-phase voltages and currents with their corresponding measured responses at the substation is achieved.
ContributorsNekkalapu, Sameer (Author) / Vittal, Vijay (Thesis advisor) / Undrill, John M (Committee member) / Ayyanar, Raja (Committee member) / Arizona State University (Publisher)
Created2018
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Description
The demand for cleaner energy technology is increasing very rapidly. Hence it is

important to increase the eciency and reliability of this emerging clean energy technologies.

This thesis focuses on modeling and reliability of solar micro inverters. In

order to make photovoltaics (PV) cost competitive with traditional energy sources,

the economies of scale have

The demand for cleaner energy technology is increasing very rapidly. Hence it is

important to increase the eciency and reliability of this emerging clean energy technologies.

This thesis focuses on modeling and reliability of solar micro inverters. In

order to make photovoltaics (PV) cost competitive with traditional energy sources,

the economies of scale have been guiding inverter design in two directions: large,

centralized, utility-scale (500 kW) inverters vs. small, modular, module level (300

W) power electronics (MLPE). MLPE, such as microinverters and DC power optimizers,

oer advantages in safety, system operations and maintenance, energy yield,

and component lifetime due to their smaller size, lower power handling requirements,

and module-level power point tracking and monitoring capability [1]. However, they

suer from two main disadvantages: rst, depending on array topology (especially

the proximity to the PV module), they can be subjected to more extreme environments

(i.e. temperature cycling) during the day, resulting in a negative impact to

reliability; second, since solar installations can have tens of thousands to millions of

modules (and as many MLPE units), it may be dicult or impossible to track and

repair units as they go out of service. Therefore identifying the weak links in this

system is of critical importance to develop more reliable micro inverters.

While an overwhelming majority of time and research has focused on PV module

eciency and reliability, these issues have been largely ignored for the balance

of system components. As a relatively nascent industry, the PV power electronics

industry does not have the extensive, standardized reliability design and testing procedures

that exist in the module industry or other more mature power electronics

industries (e.g. automotive). To do so, the critical components which are at risk and

their impact on the system performance has to be studied. This thesis identies and

addresses some of the issues related to reliability of solar micro inverters.

This thesis presents detailed discussions on various components of solar micro inverter

and their design. A micro inverter with very similar electrical specications in

comparison with commercial micro inverter is modeled in detail and veried. Components

in various stages of micro inverter are listed and their typical failure mechanisms

are reviewed. A detailed FMEA is conducted for a typical micro inverter to identify

the weak links of the system. Based on the S, O and D metrics, risk priority number

(RPN) is calculated to list the critical at-risk components. Degradation of DC bus

capacitor is identied as one the failure mechanism and the degradation model is built

to study its eect on the system performance. The system is tested for surge immunity

using standard ring and combinational surge waveforms as per IEEE 62.41 and

IEC 61000-4-5 standards. All the simulation presented in this thesis is performed

using PLECS simulation software.
ContributorsManchanahalli Ranganatha, Arkanatha Sastry (Author) / Ayyanar, Raja (Thesis advisor) / Karady, George G. (Committee member) / Qin, Jiangchao (Committee member) / Arizona State University (Publisher)
Created2015
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Description
Optical Instrument Transformers (OIT) have been developed as an alternative to traditional instrument transformers (IT). The question "Can optical instrument transformers substitute for the traditional transformers?" is the main motivation of this study. Finding the answer for this question and developing complete models are the contributions of this work. Dedicated

Optical Instrument Transformers (OIT) have been developed as an alternative to traditional instrument transformers (IT). The question "Can optical instrument transformers substitute for the traditional transformers?" is the main motivation of this study. Finding the answer for this question and developing complete models are the contributions of this work. Dedicated test facilities are developed so that the steady state and transient performances of analog outputs of a magnetic current transformer (CT) and a magnetic voltage transformer (VT) are compared with that of an optical current transformer (OCT) and an optical voltage transformer (OVT) respectively. Frequency response characteristics of OIT outputs are obtained. Comparison results show that OITs have a specified accuracy of 0.3% in all cases. They are linear, and DC offset does not saturate the systems. The OIT output signal has a 40~60 μs time delay, but this is typically less than the equivalent phase difference permitted by the IEEE and IEC standards for protection applications. Analog outputs have significantly higher bandwidths (adjustable to 20 to 40 kHz) than the IT. The digital output signal bandwidth (2.4 kHz) of an OCT is significantly lower than the analog signal bandwidth (20 kHz) due to the sampling rates involved. The OIT analog outputs may have significant white noise of 6%, but the white noise does not affect accuracy or protection performance. Temperatures up to 50oC do not adversely affect the performance of the OITs. Three types of models are developed for analog outputs: analog, digital, and complete models. Well-known mathematical methods, such as network synthesis and Jones calculus methods are applied. The developed models are compared with experiment results and are verified with simulation programs. Results show less than 1.5% for OCT and 2% for OVT difference and that the developed models can be used for power system simulations and the method used for the development can be used to develop models for all other brands of optical systems. The communication and data transfer between the all-digital protection systems is investigated by developing a test facility for all digital protection systems. Test results show that different manufacturers' relays and transformers based on the IEC standard can serve the power system successfully.
ContributorsKucuksari, Sadik (Author) / Karady, George G. (Thesis advisor) / Heydt, Gerald T (Committee member) / Holbert, Keith E. (Committee member) / Ayyanar, Raja (Committee member) / Farmer, Richard (Committee member) / Arizona State University (Publisher)
Created2010
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Description
The main objective of mathematical modeling is to connect mathematics with other scientific fields. Developing predictable models help to understand the behavior of biological systems. By testing models, one can relate mathematics and real-world experiments. To validate predictions numerically, one has to compare them with experimental data sets. Mathematical modeling

The main objective of mathematical modeling is to connect mathematics with other scientific fields. Developing predictable models help to understand the behavior of biological systems. By testing models, one can relate mathematics and real-world experiments. To validate predictions numerically, one has to compare them with experimental data sets. Mathematical modeling can be split into two groups: microscopic and macroscopic models. Microscopic models described the motion of so-called agents (e.g. cells, ants) that interact with their surrounding neighbors. The interactions among these agents form at a large scale some special structures such as flocking and swarming. One of the key questions is to relate the particular interactions among agents with the overall emerging structures. Macroscopic models are precisely designed to describe the evolution of such large structures. They are usually given as partial differential equations describing the time evolution of a density distribution (instead of tracking each individual agent). For instance, reaction-diffusion equations are used to model glioma cells and are being used to predict tumor growth. This dissertation aims at developing such a framework to better understand the complex behavior of foraging ants and glioma cells.
ContributorsJamous, Sara Sami (Author) / Motsch, Sebastien (Thesis advisor) / Armbruster, Dieter (Committee member) / Camacho, Erika (Committee member) / Moustaoui, Mohamed (Committee member) / Platte, Rodrigo (Committee member) / Arizona State University (Publisher)
Created2019