INTEGRATED MANAGEMENT OF THE INVASIVE SPECIES CIRSIUM ARVENSE, CANADA THISTLE, AND PHRAGMITES AUSTRALIS, COMMON REED: USING ECOLOGICALLY BASED CONTROL MEASURES AT EACH STAGE OF THE INVASION PROCESS

Invasive plant species threaten natural areas by reducing biodiversity and altering ecosystem functions. They also impact agriculture by reducing crop and livestock productivity. Millions of dollars are spent on invasive species control each year, and traditionally, herbicides are used to manage invasive species. Herbicides have human and environmental health risks associated with them; therefore, it is essential that land managers and stakeholders attempt to reduce these risks by utilizing the principles of integrated weed management. Integrated weed management is a practice that incorporates a variety of measures and focuses on the ecology of the invasive plant to manage it. Roadways are high risk areas that have high incidence of invasive species. Roadways act as conduits for invasive species spread and are ideal harborages for population growth; therefore, roadways should be a primary target for invasive species control. There are four stages in the invasion process which an invasive species must overcome: transport, establishment, spread, and impact. The aim of this dissertation was to focus on these four stages and examine the mechanisms underlying the progression from one stage to the next, while also developing integrated weed management strategies. The target species were Phragmites australis, common reed, and Cisrium arvense, Canada thistle. The transport and establishment risks of P. australis can be reduced by removing rhizome fragments from soil when roadside maintenance is performed. The establishment and spread of C. arvense can be reduced by planting particular resistant species, e.g. Heterotheca villosa, especially those that can reduce light transmittance to the soil. Finally, the spread and impact of C. arvense can be mitigated on roadsides through the use of the herbicide aminopyralid. The risks associated with herbicide drift produced by application equipment can be reduced by using the Wet-Blade herbicide application system.

AN ENERGY BASED MINIMUM-TIME OPTIMAL CONTROL OF DC-DC CONVERTERS

Time-optimal response is an important and sometimes necessary characteristic of dynamic systems for specific applications. Power converters are widely used in different electrical systems and their dynamic response will affect the whole system. In many electrical systems like microgrids or voltage regulators which supplies sensitive loads fast dynamic response is a must. Minimum time is the fastest converter to compensate the step output reference or load change. Boost converters as one of the wildly used power converters in the electrical systems are aimed to be controlled in optimal time in this study. Linear controllers are not able to provide the optimal response for a boost converter however they are still useful and functional for other applications like reference tracking or stabilization. To obtain the fastest possible response from boost converters, a nonlinear control approach based on the total energy of the system is studied in this research. Total energy of the system considers as the basis for developing the presented method, since it is easy and accurate to measure besides that the total energy of the system represents the actual operating condition of the boost converter. The detailed model of a boost converter is simulated in MATLAB/Simulink to achieve the time optimal response of the boost converter by applying the developed method. The simulation results confirmed the ability of the presented method to secure the time optimal response of the boost converter under four different scenarios.

MODELING AND HARDWARE-IN-THE-LOOP SIMULATION OF POWER-SPLIT HYBRID ELECTRIC VEHICLES

Conventional vehicles are creating pollution problems, global warming and the extinction of high density fuels. To address these problems, automotive companies and universities are researching on hybrid electric vehicles where two different power devices are used to propel a vehicle. This research studies the development and testing of a dynamic model for Prius 2010 Hybrid Synergy Drive (HSD), a power-split device. The device was modeled and integrated with a hybrid vehicle model. To add an electric only mode for vehicle propulsion, the hybrid synergy drive was modified by adding a clutch to carrier 1. The performance of the integrated vehicle model was tested with UDDS drive cycle using rule-based control strategy. The dSPACE Hardware-In-the-Loop (HIL) simulator was used for HIL simulation test. The HIL simulation result shows that the integration of developed HSD dynamic model with a hybrid vehicle model was successful. The HSD model was able to split power and isolate engine speed from vehicle speed in hybrid mode.

STATE OF CHARGE BASED DROOP SURFACE FOR OPTIMAL CONTROL OF DC MICROGRIDS

For a microgrid with a high penetration level of renewable energy, energy storage use becomes more integral to the system performance due to the stochastic nature of most renewable energy sources. This thesis examines the use of droop control of an energy storage source in dc microgrids in order to optimize a global cost function. The approach involves using a multidimensional surface to determine the optimal droop parameters based on load and state of charge. The optimal surface is determined using knowledge of the system architecture and can be implemented with fully decentralized source controllers. The optimal surface control of the system is presented. Derivations of a cost function along with the implementation of the optimal control are included. Results were verified using a hardware-in-the-loop system.

AGENT BASED, DISTRIBUTED CONTROL STRATEGIES AND OPTIMIZATION OF PLUG-IN ELECTRIC VEHICLES ON SMART/MICROGRID ARCHITECTURES

This thesis will present strategies for the use of plug-in electric vehicles on smart and microgrids. MATLAB is used as the design tool for all models and simulations. First, a scenario will be explored using the dispatchable loads of electric vehicles to stabilize a microgrid with a high penetration of renewable power generation. Grid components for a microgrid with 50% photovoltaic solar production will be sized through an optimization routine to maintain storage system, load, and vehicle states over a 24-hour period. The findings of this portion are that the dispatchable loads can be used to guard against unpredictable losses in renewable generation output. Second, the use of distributed control strategies for the charging of electric vehicles utilizing an agent-based approach on a smart grid will be studied. The vehicles are regarded as additional loads to a primary forecasted load and use information transfer with the grid to make their charging decisions. Three lightweight control strategies and their effects on the power grid will be presented. The findings are that the charging behavior and peak loads on the grid can be reduced through the use of distributed control strategies.

LOCAL DIGITAL CONTROL OF POWER ELECTRONIC CONVERTERS IN A DC MICROGRID BASED ON A-PRIORI DERIVATION OF SWITCHING SURFACES

In power electronic basedmicrogrids, the computational requirements needed to implement an optimized online control strategy can be prohibitive. The work presented in this dissertation proposes a generalized method of derivation of geometric manifolds in a dc microgrid that is based on the a-priori computation of the optimal reactions and trajectories for classes of events in a dc microgrid. The proposed states are the stored energies in all the energy storage elements of the dc microgrid and power flowing into them. It is anticipated that calculating a large enough set of dissimilar transient scenarios will also span many scenarios not specifically used to develop the surface. These geometric manifolds will then be used as reference surfaces in any type of controller, such as a sliding mode hysteretic controller. The presence of switched power converters in microgrids involve different control actions for different system events. The control of the switch states of the converters is essential for steady state and transient operations. A digital memory look-up based controller that uses a hysteretic sliding mode control strategy is an effective technique to generate the proper switch states for the converters. An example dcmicrogrid with three dc-dc boost converters and resistive loads is considered for this work. The geometric manifolds are successfully generated for transient events, such as step changes in the loads and the sources. The surfaces corresponding to a specific case of step change in the loads are then used as reference surfaces in an EEPROM for experimentally validating the control strategy. The required switch states corresponding to this specific transient scenario are programmed in the EEPROM as a memory table. This controls the switching of the dc-dc boost converters and drives the system states to the reference manifold. In this work, it is shown that this strategy effectively controls the system for a transient condition such as step changes in the loads for the example case.