Methods of analysis and important design considerations for distributed power systems (DPS) are addressed. A generalized analysis of subsystem interaction is presented. Emphasis is placed on absolute stability and eigenvalue location of the integrated system. Terminal properties of the decoupled subsystems are used in determining the stability criteria. Either analytical models or empirical data may be used in the interaction analysis. Design of EMI filters for a two-stage DPS is comprehensively discussed. A detailed analysis of the effects of input filters on current-mode controlled single-module regulators is given. It is shown that the criteria used to minimize filter interaction for voltage-mode and current-mode controlled regulators are identical. The results of the single-module regulator input filter interaction analysis are extended to the multi-module DPS case. Both line input filters and intermediate bus filters are designed for stability and to minimize interaction with the regulator modules. Implications of non-minimal dimensional subsystems are discussed. The eigenvalues due to parallel interaction are described, and it is shown how appropriate damping can be used to insure their stability. Straight-forward design guidelines are provided for the filters. Interaction of a non-ideal generator source with the DPS is described. This provides a useful application of the general subsystem interaction analysis. Stability is determined from different points in the system, and subsystem impedances are used to qualitatively describe the integrated system eigenvalue location. / Master of Science

by Li Pak Cheong. / Thesis (M.B.A.)--Chinese University of Hong Kong, 1980. / Bibliography: leaf 82.

Thesis (Ph.D.)--University of Canterbury, 2009. / Typescript (photocopy). "March 2009." "Supervisors: Professor Les Oxley and Professor John Gibson." Includes bibliographical references (p. 325-359). Also available via the World Wide Web.

published_or_final_version / Urban Planning / Master / Master of Science in Urban Planning

Five diagrams in pocket.

Spectrally selective designs (SSDs), which selectively reflect, transmit, absorb or radiate light depending on the wavelength, impact our lives in many ways. For instance, precisely designed metasurfaces on silicon offer unprecedented control of light in the visible and infrared wavelengths. A less sophisticated example, white paints, simultaneously reflect sunlight and radiate heat to passively cool buildings. SSDs like these are meaningful scientific pursuits as well as socially impactful in their applications. However, the latter is not always the case, as prioritization of novelty and performance in research have often led to SSDs whose sophistication and cost restricts their use. Furthermore, given increasing concerns about cost, eco-friendliness and applicability in the developing world, designs that overcome such issues are becoming increasingly sought-after. The works presented here aim to address this gap between high performance and applicability by combining scientific principles with the use of common materials and simple techniques to create SSDs for optical and energy applications. The work is categorized under three chapters. The first of these involve solution-derived nanostructured metal surfaces as a plasmonic platform for solar, thermal and optical applications. The second is concerned with porous polymers for passive daytime radiative cooling. The third and last chapter involves porous polymer coatings for switchable optical and thermal management. Prior to these sections, a general introduction to the fundamentals related to the topics – e.g. solar and thermal radiation, plasmon resonances in nanoparticles and electromagnetic scattering of light – are presented. The works in the three aforementioned sections are briefly summarized below. For the work on plasmonic nanostructured metal surfaces, a galvanic-displacement-reaction-based, room-temperature “dip-and-dry” technique is demonstrated for fabricating plasmonic-nanoparticle-coated foils (PNFs). The technique involves simply dipping a metal (M1) foil onto an aqueous salt of a less reactive metal (M2), and allowing the spontaneously resulting chemical reaction to form plasmonic nano or microparticles of M2 to form on M1. By controlling reaction parameters such as time, temperature and salt concentration, the reflectance spectrum of the PNFs can be tuned across the solar to far infrared wavelengths (0.35 – 20 μm). Consequently, the technique can tune the PNFs solar absorptance (~0.35 to 0.98) and thermal emittance (~0.05 to ~0.95). This is promising for applications such as selective solar absorption, selective thermal infrared emission, super-broadband thermal absorbers and emitters, and radiative cooling. The potential for selective solar absorption is investigated in detail, with the technique tuned to yield copper nanoparticle-coated Zinc substrate with excellent, wide-angle solar absorptance (0.96 at 15°, to 0.97 at 35°, to 0.79 at 80°), and low hemispherical thermal emittance (< 0.10). Issues important for applications, such as mechanical and thermal stability of the PNFs, are also investigated. The work on porous polymers for radiative cooling investigates the effect of porosity on the optical properties of polymers. Typically, polymers are intrinsically non-absorptive in the solar (0.35-2.5 μm), and emissive in one or more bands within the thermal infrared (2.5-20 μm) wavelengths. When made porous, the voids within the polymer can lead to different optical behaviors depending on their size. For instance, air voids with sizes (~1 μm) similar to solar wavelengths scatter sunlight due to the refractive index contrast between the polymer and air, leading to a high solar reflectance. Nanoscale (~0.1 μm) air voids, which are much smaller than longer thermal wavelengths (> 2.5 μm), lower the effective refractive index of the polymer in those wavelengths and increase thermal emittance. Porous polymer coatings (PPCs) with such air voids and optical properties can be made by scalable, solution-based and paint-like processes such as phase inversion. For example, phase-inverted poly(vinylidene fluoride-co-hexafluoropropene) (P(VdF-HFP)) exhibit an exceptional solar reflectance of up to 0.99 and hemispherical long-wave infrared emittance ~ 0.97. This allows the P(VdF-HFP) PPCs to achieve a net heat loss and reach sub-ambient temperatures of 6˚C even at noon. This passive radiative cooling performance, which surpasses those of notable designs in the literature, is obtained with a paint like convenience – making it promising as a sustainable cooling solution for buildings. The work on switchable optical and thermal management is related to the work above, and shows that optical performance of PPCs can also be altered by replacing the air in the pores with commonly available liquids. For instance, wetting PPCs with a liquid having the same solar refractive index as the polymer reduces optical scattering and turns the PPCs from white to transparent. Thermally transparent PPCs, meanwhile, turn absorptive or emissive when wetted with infrared-absorptive liquids. Both of these transitions can be reversed by drying – yielding a scalable and low-cost optical switching paradigm for solar and thermal wavelengths. The switchable optical transmittance can be useful in a wide variety of applications, such as controlling daylight in buildings, tunable solar heating and radiative cooling, water responsive systems and thermal camouflage. The works presented above attempt to achieve a desirable balance between scientific novelty, performance, simplicity and cost, with the intention of bringing high-performing optical designs to low-resource settings in the developing world. While this dissertation is a small step towards that goal, the author hopes that the readers will find the content to be of value.

An assessment of the thermal resource in the Straits of Florida was performed to estimate the Ocean Thermal Energy Conversion (OTEC) potential. Direct measurements of the temperature profile across the Florida Straits were taken from nearshore Southeast Florida to the Exclusive Economic Zone boundary along four evenly spaced transects perpendicular to Florida's Southeast coast, spanning 160 km. Along the southern transects in summer, nearshore cold and warm water resources meet or exceed the average 20ÀC temperature difference required for OTEC. In winter, the nearshore average DT of 17.76ÀC can produce 59-75% design net power and 70-86% in spring with DT averaging 18.25ÀC. Offshore along the southern transects, a high steady DT from 18.5- 24ÀC creates an annual average net power of 120-125MW. Along the northern transects, the nearshore resource does not exist, but a consistent OTEC resource is present offshore, providing 70-80% design net power in winter, and 100-158% in spring and summer. / by Anna E. Leland. / Thesis (M.S.C.S.)--Florida Atlantic University, 2009. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2009. Mode of access: World Wide Web.

Electricity demand is rapidly increasing with growth of population, development of technologies and electrically intensive industries. Also, emerging climate change concerns compel governments to seek environmentally friendly ways to produce electricity such as wind energy systems. In 2018, the wind energy reached 600 GW total capacity globally. However, this corresponds to only about 6% of global electricity demand and there is a need to increase wind energy penetration in electricity grids. One way to enhance the competitiveness of wind energy is to improve its reliability and availability and reduce associated maintenance costs. This study utilizes a database entitled “Wind Monitor and Evaluation Program (WMEP)” to investigate, model and improve wind turbine reliability and availability. The WMEP database consists of maintenance data of 575 wind turbines in Germany during 1989-2008. It is unique as it includes details of turbine model and size, affected subsystem and component, cause of failure, date and time of maintenance, location, and energy production from the wind turbines. Additional parameters such as climatic regions, geography number of previous failures and mean annual wind speed are added to the database in this study. In this research, two metrics are considered and developed such as time-to-failure or failure rate and time-to-repair or downtime for reliability and availability, respectively. This study investigated failure causes, effects and criticalities of wind turbine subsystems and components, assessed the risk factors impacting wind turbine reliability, modeled the reliability of wind turbines based on assessed risk factors, and predicted the cost of wind turbine failures under various operational and environmental conditions. A well-established reliability assessment technique - Failure Modes, Effects and Criticality Analysis is applied on the WMEP maintenance data from 109 wind turbines and three different climatic regions to understand the impacts of climate and wind turbine design type on wind turbine reliability and availability. First, climatic region impacts on identical wind turbine failures are investigated, then impacts of wind turbine design type are examined for the same climatic region. Furthermore, we compared the results of this investigation with results from previous FMECA studies which neglected impacts of climatic region and turbine design type in section 5.4. Two-step cluster and survival analyses are used to determine risk factors that affect wind turbine reliability. Six operational and environmental factors are considered for this approach, namely capacity factor (CF), wind turbine design type, number of previous failures (NOPF), geographical location, climatic region and mean annual wind speed (MAWS). Data are classified as frequent (time-to-failure<40 days) and non-frequent (time-to-failure>80 days) failures and we identified 615 operations listing all these factor and energy production from 21 wind turbines in the WMEP data base. These factors are examined for their impact on wind turbine reliability and results are compared. In addition, wind turbine reliability is modeled by machine learning methods, namely logistic regression (LR) and artificial neural network (ANN), using the considered 615 operations. The objective of this investigation is to model and predict probability of frequently-failing wind turbines based on wind turbines’ known operational and environmental conditions. The models are evaluated and cross validated with 10-fold cross validation and prediction performances and compared with other algorithms such as k-nearest neighbor and support vector machines. Also, prediction performances of LR and ANN are discussed along with their easiness to interpret and share with others. Lastly, using data from 753 operations, a decision support tool for predicting cost of wind turbine failures is developed. The tool development includes machine learning application for estimating probability of failures in 60 days of operation and time-to-repair probabilities for divisions of 0-8hrs, 8-16hrs, 16-24hrs and more than 1 day based on operational and environmental conditions of wind turbines. Prediction for cost of wind turbine failures for 60 days of operation is calculated using assumed costs from time-to-repair divisions. The decision support tool can be updated by the user’s discretion on the cost of failures. This study provides a better understanding of wind turbine failures by investigating associated risk factors, modeling wind turbine reliability and predicting the future cost of failures by applying state-of-the art reliability and data analysis techniques. Wind energy developers and operators can be guided by this study in improving the reliability of wind turbines. Also, wind energy investors, operators and maintenance service managers can predict the cost of wind turbine failures with the decision support tool provided in this study.

The following study explores the worldwide spatial and temporal distributions of electrical power that can be extracted from the ocean's stored solar energy via the process of closed-cycle ocean thermal energy conversion (OTEC). Special emphasis is placed on resources surrounding the state of Florida. The study combines oceanographic input from a state-of-the-art ocean circulation model, the Hybrid Coordinate Ocean Model, with a state-of-the-industry OTEC plant model to predict achievable power values across the world. These power predictions are then constrained by local replenishment rates of cold deep sea water to provide an upper limit to the sustainable OTEC resource. Next, the geographic feasibility of OTEC-coupled and OTEC-independent sea water cooling (air conditioning and refrigeration) are explored. Finally, the model data is validated against in situ oceanic measurements to ensure the quality of the predictions. / by Lynn Rauchenstein. / Thesis (M.S.C.S.)--Florida Atlantic University, 2012. / Includes bibliography. / Mode of access: World Wide Web. / System requirements: Adobe Reader.

Typescript (photocopy). / Digitized by Kansas Correctional Industries