<p> Zero Net Energy Buildings (ZNEB) are gaining popularity, and many governments want commercial ZNEB status in a decade from now. This project uses the energy consumption data of California State University, Long Beach (CSULB) to design a ZNEB system for the CSULB-Alumni Center. The campus energy data is taken and averaged by considering the number of buildings. Various Energy Efficiency Measures (EEMs) such as scheduled operation of equipment and advanced lighting were considered in designing the ZNEB Alumni Center. The ZNEB System building design is in two different configurations: 1) A system with solar Photo Voltaic (PV); 2) A system with solar PV and a Battery Energy Storage System. The Hybrid Optimization Model for Electric Renewables (HOMER) software simulates the ZNEB Alumni Center. Two configurations are compared in terms of payback and Net Present Value (NPV). The system with the highest NPV and early payback is considered the optimal system.</p>

<p> For the long-term strategy of gradual decarbonization of the world&rsquo;s energy supply, high penetration of PV electricity is critical in the future world energy landscape. In order to achieve this, solar electricity with competitive cost to fossil fuel energy is necessary. To be able to obtain high efficiency solar cells, many advanced cell architectures have been developed commercially by PV industry. However, the fabrication of these cells necessitates complex processing steps and high requirements on semiconductor materials, which make it not as cost-effective as the state-of-the-art conventional Al-BSF structure. In order to keep the cost of PV cell low and improve on the efficiency with fewer processing steps, this thesis work focuses on the understanding of the conventional Al-BSF solar cell structure. The research work therefore, focuses on the (i) design, and modeling of front metal electrodes including the use of multi-bus-bar capable of decreasing the gridline resistance, (ii) fine-line printing and (iii) metal contact co-firing using high belt speed that is not common to the solar industry to achieve ~20% efficient industrial Al-BSF silicon solar cells.</p><p> In order to achieve the objectives of this thesis work, firstly, the appropriate Al paste was investigated for lowest back surface recombination velocity (BSRV), which gives high open circuit voltage (V_oc). Secondly, the impact of emitter sheet resistance on solar cell performance was modeled to determine the optimal sheet resistance, and the uniformity of emitter was also investigated. Thirdly, modeling on the front metal electrodes was carried out to investigate the optimal number of busbars, and determine the optimum number of gridlines and gridline geometries that would result in low series resistance (R_s), high fill factor (FF) and hence high efficiency. Fourthly, the modeled results were experimentally validated through fine-line printing and optimized contact co-firing. By combining each layer to make solar cells, V_oc of ~642 mV, J_sc of ~38.5 mA/cm² and FF of ~80.4% led to average ~19.8% efficient cell. Based on the experimental results, other innovative front grid designs are proposed that can lead to >20% energy conversion efficiency.</p>

<p> This thesis focuses on the static optimization of a fuel cell plug-in hybrid electric vehicle. The vehicle is been powered by three (3) sources of electrical energy. These sources of electrical energy are: fuel cell, supercapacitor, and lithium-ion battery. </p><p> The main target of this thesis is to make good the performance of a fuel cell plug-in hybrid electric vehicle. This will be achieved by applying static optimization method on the dynamic equations of a moving hybrid vehicle. </p><p> The optimization model of this plug-in hybrid electric vehicle (PHEV) was formulated bases on multiple objectives. The objective parameters are: cost, volume, and mass. We were able to apply static optimization algorithm to find optimal solutions for both the objective values and decision variables of the multiple energy sources. </p><p> The optimization model formulated from the dynamic equations, objective specifications, and design constrains were found to be feasible, bounded, and optimizable by subjecting the primal optimization model to its equivalent dual optimization test. </p><p> Advanced vehicle simulator (ADVISOR) was used to stimulate vehicle performance of our design on a standard driving cycle. The results provide a better outcome than that of standard driving cycles.</p><p>

<p>Solar photovoltaics (PV), the technology that converts sunlight into electricity, has immense potential to become a significant electricity source. Nevertheless, the laws of economics dictate that to grow from the current 2% of U.S. electricity generation and to achieve large scale adoption of solar PV, the cost needs to be reduced to the point where it achieves grid parity. For silicon solar cells, which form 90% of the PV market, a significant and slowly declining component of the cost is due to the high-temperature (> 900 &deg;C) processing required to form p-n junctions. In this thesis, the replacement of the high-temperature p-n junction with a low-temperature amorphous titanium dioxide (TiO₂)/silicon heterojunction is investigated. The TiO₂/Si heterojunction forms an electron-selective, hole-blocking contact. A chemical vapor deposition method using only one precursor is utilized, leading to a maximum deposition condition of 100 &deg;C. High-quality passivation of the TiO₂/Si interface is achieved, with a minimum surface recombination velocity of 28 cm/s. This passivated TiO₂ is used in a double-sided PEDOT/n-Si/TiO₂ solar cell, demonstrating an open-circuit voltage increase of 45 mV. Further, a heterojunction bipolar transistor (HBT) method is developed to investigate the current mechanisms across the TiO₂/p-Si heterojunction, leading to the determination that 4nm of TiO₂ provides the optimal thickness. And finally, an analytical model is developed to explain the current mechanisms observed across the TiO₂/Si interface. From this model, it is determined that once &#916;E_V (TiO₂/Si) is large enough (400 meV), the two key parameters are the Schottky barrier height (resulting in band-bending in silicon) and the recombination velocity at the TiO₂/Si interface. Data corroborates this, indicating the hole-blocking mechanism is due to band-bending induced by the unpinning of the Al/Si interface and TiO₂ charge, as opposed to due to the TiO₂ valence band edge.

<p> This dissertation introduces hardware-in-the-loop modeling and simulation techniques to the daylighting community, with specific application to complex fenestration systems. No such application of this class of techniques, optimally combining mathematical-modeling and physical-modeling experimentation, is known to the author previously in the literature. </p><p> Daylighting systems in buildings have a large impact on both the energy usage of a building as well as the occupant experience within a space. As such, a renewed interest has been placed on designing and constructing buildings with an emphasis on daylighting in recent times as part of the "green movement.'' </p><p> Within daylighting systems, a specific subclass of building envelope is receiving much attention: complex fenestration systems (CFSs). CFSs are unique as compared to regular fenestration systems (e.g. glazing) in the regard that they allow for non-specular transmission of daylight into a space. This non-specular nature can be leveraged by designers to "optimize'' the times of the day and the days of the year that daylight enters a space. Examples of CFSs include: Venetian blinds, woven fabric shades, and prismatic window coatings. In order to leverage the non-specular transmission properties of CFSs, however, engineering analysis techniques capable of faithfully representing the physics of these systems are needed. </p><p> Traditionally, the analysis techniques available to the daylighting community fall broadly into three classes: simplified techniques, mathematical-modeling and simulation, and physical-modeling and experimentation. Simplified techniques use "rules-of-thumb'' heuristics to provide insights for simple daylighting systems. Mathematical-modeling and simulation use complex numerical models to provide more detailed insights into system performance. Finally, physical-models can be instrumented and excited using artificial and natural light sources to provide performance insight into a daylighting system. Each class of techniques, broadly speaking however, has advantages and disadvantages with respect to the cost of execution (e.g. money, time, expertise) and the fidelity of the provided insight into the performance of the daylighting system. This varying tradeoff of cost and insight between the techniques determines which techniques are employed for which projects. </p><p> Daylighting systems with CFS components, however, when considered for simulation with respect to these traditional technique classes, defy high fidelity analysis. Simplified techniques are clearly not applicable. Mathematical-models must have great complexity in order to capture the non-specular transmission accurately, which greatly limit their applicability. This leaves physical modeling, the most costly, as the preferred method for CFS. While mathematical-modeling and simulation methods do exist, they are in general costly and and still approximations of the underlying CFS behavior. Meaning in fact, measurements of CFSs are currently the only practical method to capture the behavior of CFSs. Traditional measurements of CFSs transmission and reflection properties are conducted using an instrument called a goniophotometer and produce a measurement in the form of a Bidirectional Scatter Distribution Function (BSDF) based on the Klems Basis. This measurement must be executed for each possible state of the CFS, hence only a subset of the possible behaviors can be captured for CFSs with continuously varying configurations. In the current era of rapid prototyping (e.g. 3D printing) and automated control of buildings including daylighting systems, a new analysis technique is needed which can faithfully represent these CFSs which are being designed and constructed at an increasing rate. </p><p> Hardware-in-the-loop modeling and simulation is a perfect fit to the current need of analyzing daylighting systems with CFSs. In the proposed hardware-in-the-loop modeling and simulation approach of this dissertation, physical-models of real CFSs are excited using either natural or artificial light. The exiting luminance distribution from these CFSs is measured and used as inputs to a Radiance mathematical-model of the interior of the space, which is proposed to be lit by the CFS containing daylighting system. Hence, the components of the total daylighting and building system which are not mathematically-modeled well, the CFS, are physically excited and measured, while the components which are modeled properly, namely the interior building space, are mathematically-modeled. In order to excite and measure CFSs behavior, a novel parallel goniophotometer, referred to as the CUBE 2.0, is developed in this dissertation. The CUBE 2.0 measures the input illuminance distribution and the output luminance distribution with respect to a CFS under test. Further, the process is fully automated allowing for deployable experiments on proposed building sites, as well as in laboratory based experiments. </p><p> In this dissertation, three CFSs, two commercially available and one novel&mdash;Twitchell's Textilene 80 Black, Twitchell's Shade View Ebony, and Translucent Concrete Panels (TCP)&mdash;are simulated on the CUBE 2.0 system for daylong deployments at one minute time steps. These CFSs are assumed to be placed in the glazing space within the Reference Office Radiance model, for which horizontal illuminance on a work plane of 0.8 m height is calculated for each time step. While Shade View Ebony and TCPs are unmeasured CFSs with respect to BSDF, Textilene 80 Black has been previously measured. As such a validation of the CUBE 2.0 using the goniophotometer measured BSDF is presented, with measurement errors of the horizontal illuminance between +3% and -10%. These error levels are considered to be valid within experimental daylighting investigations. Non-validated results are also presented in full for both Shade View Ebony as well as TCP. </p><p> Concluding remarks and future directions for HWiL simulation close the dissertation.</p><p>

<p> Due to the increased demand for reliable and resilient controls in advanced power generation systems, new control methods are required to tackle traditional problems within these systems. This work discusses a control method and an estimation method for advanced control systems. The control method is sliding mode controls of a higher order, which is used to control the nonlinear wind energy conversion system while lessening the chattering phenomena that causes mechanical wear when using first order sliding mode controls. The super-twisting algorithm is used to create a second order sliding mode control. The estimation method is the derivation of a Resilient Extended Kalman filter, which can estimate and control the system through sensor undergoing failures with a binomial distribution rate and known mean value. Simulations on these dynamical systems are presented to show the effectiveness of the proposed control methods; the former is applied to a wind energy conversion system and the latter is applied to an single machine infinite bus. Both methods are also compared with more traditional methods in their respective applications, those being first order sliding mode controls and the Extended Kalman filter. </p><p>

Wind power is an attractive additional source of energy in an isolated electric power system consisting of a diesel powered generator and consumer load. When a small wind turbine is added the resulting wind/diesel system works well. The addition of a larger wind turbine may significantly influence the dynamic behavior of the entire system. This dissertation studies the dynamics of a wind/diesel system with no storage. A method to easily examine the dynamic effects of both system and wind turbine sizing is presented. A mathematical model of wind/diesel systems is developed and then generalized using per-unit scaling. Ranges of values for per-unit parameters in the wind/diesel system model, and their relationship to component size is established. The model is implemented in the simulation software called Advanced Continuous Simulation Language. With the computer model the sensitivity of system dynamics to parameter variation, component sizing, and system size is found. In addition, the performance of various governors and voltage regulators is studied. The inertia of the diesel is found to have a strong influence on dynamic behavior of the system. Increasing wind turbine size decreases system damping and slows system dynamics. Increasing system size also decreases damping, but the dominant open loop characteristic frequency of the system increases. Recommendations of how the model developed might be expanded are given.

<p> Environmental concerns are driving the automotive industry towards more sustainable and efficient forms of transportation such as electric vehicles. The electric drivetrains present in the various types of electric vehicles are much more efficient than traditional internal combustion engine drivetrains and produce fewer greenhouse gases. The most popular type of motor used in electric vehicle drivetrains is the permanent magnet synchronous motor. This can be attributed to its inherent high power density, large torque to weight ratio, and high reliability and efficiency. Advanced control techniques for permanent magnet synchronous motor drives must be developed in order to meet the high performance and efficiency demands of modern electric vehicles. Application of the nonlinear control method known as sliding mode control is the focus of this work. Both first order and higher order sliding mode methods are considered. These control methods provide robustness to modeling inaccuracies, internal parameter variations, and external disturbances. In addition to permanent magnet synchronous motors, the sliding mode control methods are also applied to the buck-boost type DC-DC converter. DC-DC converters have found extensive applications, ranging from consumer electronics to electric vehicles and smart grid synchronization. Computer simulation studies verify the efficacy of the proposed control techniques.</p>

<p> Wind turbines typically rely on feedback controllers to maximize power capture in below-rated conditions and regulate rotor speed during above-rated operation. However, measurements of the approaching wind provided by Light Detection and Ranging (lidar) can be used as part of a preview-based, or feedforward, control system in order to improve rotor speed regulation and reduce structural loads. But the effectiveness of preview-based control depends on how accurately lidar can measure the wind that will interact with the turbine. </p><p> In this thesis, lidar measurement error is determined using a statistical frequency-domain wind field model including wind evolution, or the change in turbulent wind speeds between the time they are measured and when they reach the turbine. Parameters of the National Renewable Energy Laboratory (NREL) 5-MW reference turbine model are used to determine measurement error for a hub-mounted circularly-scanning lidar scenario, based on commercially-available technology, designed to estimate rotor effective uniform and shear wind speed components. By combining the wind field model, lidar model, and turbine parameters, the optimal lidar scan radius and preview distance that yield the minimum mean square measurement error, as well as the resulting minimum achievable error, are found for a variety of wind conditions. With optimized scan scenarios, it is found that relatively low measurement error can be achieved, but the attainable measurement error largely depends on the wind conditions. In addition, the impact of the induction zone, the region upstream of the turbine where the approaching wind speeds are reduced, as well as turbine yaw error on measurement quality is analyzed.</p><p> In order to minimize the mean square measurement error, an optimal measurement prefilter is employed, which depends on statistics of the correlation between the preview measurements and the wind that interacts with the turbine. However, because the wind speeds encountered by the turbine are unknown, a Kalman filter-based wind speed estimator is developed that relies on turbine sensor outputs. Using simulated lidar measurements in conjunction with wind speed estimator outputs based on aeroelastic simulations of the NREL 5-MW turbine model, it is shown how the optimal prefilter can adapt to varying degrees of measurement quality. </p>

In this dissertation, I develop a new theoretical framework for the modeling, pricing analysis, and computation of solutions to electric power supply chains with power generators, suppliers, transmission service providers, and the inclusion of consumer demands. In particular, I advocate the application of finite-dimensional variational inequality theory, projected dynamical systems theory, game theory, network theory, and other tools that have been recently proposed for the modeling and analysis of supply chain networks (cf. Nagurney (2006)) to electric power markets. This dissertation contributes to the extant literature on the modeling, analysis, and solution of supply chain networks, including global supply chains, in general, and electric power supply chains, in particular, in the following ways. It develops a theoretical framework for modeling, pricing analysis, and computation of electric power flows/transactions in electric power systems using the rationale for supply chain analysis. The models developed include both static and dynamic ones. The dissertation also adds a new dimension to the methodology of the theory of projected dynamical systems by proving that, irrespective of the speeds of adjustment, the equilibrium of the system remains the same. Finally, I include alternative fuel suppliers, along with their behavior into the supply chain modeling and analysis framework. This dissertation has strong practical implications. In an era in which technology and globalization, coupled with increasing risk and uncertainty, complicate electricity demand and supply within and between nations, the successful management of electric power systems and pricing become increasingly pressing topics with relevance not only for economic prosperity but also national security. This dissertation addresses such related topics by providing models, pricing tools, and algorithms for decentralized electric power supply chains. This dissertation is based heavily on the following coauthored papers: Nagurney, Cruz, and Matsypura (2003), Nagurney and Matsypura (2004, 2005, 2006), Matsypura and Nagurney (2005), Matsypura, Nagurney, and Liu (2006).