Techn. Univ., Diss.--München, 2002.

Thesis (M.S.)--University of Missouri--Rolla, 2007. / Vita. The entire thesis text is included in file. Title from title screen of thesis/dissertation PDF file (viewed October 25, 2007) Includes bibliographical references (p. 61-62).

It has been estimated that 15 million individuals around the world experience the ill effects of neural disabilities every year. Neural disabilities can affect motor control, such as Locked in Syndrome or Amyotrophic Lateral Sclerosis, whereas other affect working memory, such as schizophrenia, Alzheimer's and Parkinson's. However, recent research has show that mental rehearsal of physical movement tasks may remain intact following higher centre damage, and as such represents a new opportunity to accessing the motor system and using it to control devices. Brain Computer Interfaces (BCI) captures the brain's electrical activity and translates it into real time electrical outputs, independent of the orthodox output pathways of peripheral nervous system and muscles. Utilising the brain's electrical activity BCI has the potential to significantly enhance the lives of many individuals suffering from neurological disorders. Unfortunately, the electrical activity associated with motor activity in these individuals can be lower than normal, with acute cortical infarcts decreasing the alpha wave oscillations for the affected pericentral sensorimotor areas. This has brought into doubt whether the intensity of brain signals in these individuals can be large enough to be used as a BCI system control signal for biofeedback training. This thesis aims to examine both if alternative EEG signal can be used and if externally applied neuromodulation can facilitate the process.

This research investigates the modeling and simulation, using the state transition approach to nonlinear system simulation, of a DC drive system. The drive system that was modeled is a closed loop system composed of a velocity loop with an inner current loop. The power stage is composed of a pulse generator module and a scr bridge, while the motor is a permanent magnet DC motor. A detailed development of each module model is included to reveal the open loop characteristics of the system. A total system state model was developed from each of the modules and closed loop simulations were run. The results show that the system may be modeled and simulated using this technique. However, the exactness of the simulation is heavily dependent on the DC motor parameters selected for the model. / Master of Science

In the modern power grid, the increasing penetration of intermittent energy sources like solar and wind into the comes with unsought challenges. With increasing smart grid directcurrent (DC) deployments in distribution feeders, microgrids, smart buildings, and highvoltage transmission, there is a need for better understanding the landscape of power flow (PF) solutions as well as for efficient PF solvers with performance guarantees. This thesis puts forth three approaches with complementary strengths towards coping with the PF task, consisting of solving a system on non-linear equations, in DC power systems. We consider a possibly meshed network hosting ZIP loads and constant-voltage/power generators. Uncertainty is another inevitable side-effect of a modern power grid with vast deployments of renewable generation. Since energy storage systems (ESS) can be employed to mitigate the effect of uncertainties, their energy and power ratings along with their charging control strategies become of vital importance for renewable energy producers. This thesis also deals with the task of sizing ESS under a model predictive control (MPC) operation for a single ESS used to smoothen out a random energy signal. To account for correlations in the energy signal and enable charging adjustments in response to real-time fluctuations, we adopt a linear charging policy, designed by minimizing the initial ESS investment plus the average operational cost. Since charging decisions become random, the energy and power limits are posed as chance constraints. The chance constraints are enforced in a distributionally robust fashion. The proposed scheme is contrasted to a charging policy under Gaussian uncertainties and a deterministic formulation. / M.S. / Power systems are undergoing major changes as more renewable energy resources are being deployed across their networks. Two of the major changes are the increase in direct-current (DC) generation and loads and making up for the uncertainty introduced by these resources. In this thesis, we have tackled these two important aspects; a DC power flow (PF) solver and an energy storage system (ESS) sizing under uncertainty. The three DC PF solvers proposed in this thesis exhibit complementary values and can handle a wide range of loads and generation types. We have also proposed a distributionally robust ESS sizing under model predictive control framework, capable of handling worst-case uncertainties.

The thesis shows a simplified representation for an armature rectifier driving a DC motor load. This representation was obtained from the nonlinear equations relating the output current of the armature rectifier into the DC motor as a function of the input control variable for continuous and discontinuous current conduction. Using this simplified representation, a velocity regulator with gears connecting the DC motor to an inertia load was examined by the Bode diagram method to observe the effects of twist in the load shaft and backlash in the gears on the stability of the velocity regulator. Velocity damping and friction were neglected in the analysis. It was discovered that the armature rectifier operating in discontinuous current presented stability problems which are not encountered in a velocity regulator using a conventional rotating armature supply to drive a DC motor. Linear stabilization techniques were used to stabilize the control system to overcome the effects of twist in the load shaft and backlash in the gears for both continuous and discontinuous conduction of the armature rectifier. / M.S.

published_or_final_version / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy

No description available.

Master of Science / Department of Architectural Engineering and Construction Science / Fred Hasler / This paper discusses a brief history of electricity, specifically alternating current (AC) and direct current (DC), and how the current standard of AC distribution has been reached. DC power was first produced in 1800, but the shift to AC occurred in the 1880’s with the advent of the transformer. Because the decisions for distribution were made over 100 years ago, it could be time to rethink the standards of power distribution. Compared to traditional AC distribution, DC microgrids are significantly more energy efficient when implemented with distributed generation. Distributed generation, or on-site generation from photovoltaic panels, wind turbines, fuel cells, or microturbines, is more efficient when the power is transmitted by DC. DC generation, paired with the growing DC load profile, increases energy savings by utilizing DC architecture and eliminating wasteful conversions. Energy savings would result from a lower grid strain and more efficient utilization of the utility grid. DC distribution results in a more reliable electrical service due to short transmission distances, high service reliability when paired with on-site generation, and efficient storage. Occupant safety is a perceived concern with DC microgrids due to the lack of knowledge and familiarity in regards to these systems. However, with proper regulation and design standards, building occupants never encounter voltage higher than 24VDC, which is significantly safer than existing 120VAC in the United States. DC Microgrids have several disadvantages such as higher initial cost due, in part, to unfamiliarity of the system as well as a general lack of code recognition and efficiency metric recognition leading to difficult certification and code compliance. Case studies are cited in this paper to demonstrate energy reduction possibilities due to the lack of modeling ability in current energy analysis programs and demonstrated energy savings of approximately 20%. It was concluded that continued advancement in code development will come from pressure to increase energy efficiency. This pressure, paired with the standardization of a 24VDC plug and socket, will cause substantial increases in DC microgrid usage in the next 10 years.

published_or_final_version / abstract / Electrical and Electronic Engineering / Doctoral / Doctor of Philosophy