QUANTIFYING UNCERTAINTIES AND RISKS ASSOCIATED WITH HYDROMETEROLOGICAL VARIABLES FOR BULK ELECTRIC POWER SYSTEMS AND MARKET PARTICIPANTS

The electrical power industry is changing rapidly. From the deregulation of power markets to the rapid increase of renewable energy penetration, over the past decade power systems have witnessed major shifts in technology, regulation and policy. These rapid transitions make the use of historical performance data a fundamentally unreliable approach to evaluate reliability and financial risks for industry participants, including utilities. This is especially true with respect to performance risks stemming from uncertainty in hydrometeorological conditions (e.g., temperature, precipitation, wind, solar irradiance), which is itself difficult to characterize due to relatively short historical records. Hydrometeorological conditions are known to influence the operations of bulk electric power systems and wholesale markets for electricity, creating a source of risk for system participants. Streamflow is the “fuel” for hydropower generation, wind speeds and solar irradiance dictate the availability of wind and solar power production, and air temperatures strongly affect heating and cooling demands. Yet, despite growing concern about the vulnerability of power systems to hydrometeorological uncertainty, few studies have been able to experimentally study the full extent of the supply and financial risks that hydrometerological factors impose on power systems. This research focuses on quantitative characterization of the physical, environmental and financial risks posed by uncertain hydrometerological variables in a major segment of the U.S. power sector. Using the U.S. West Coast bulk power system as a test bed, this dissertation first develops an open source simulation framework capable of simulating the operations of California’s wholesale market under hydrometeorological uncertainty, including events outside the historical record. The second part of this dissertation uses a 1000-year stochastic simulation of the power model to probabilistically explore the market risks associated with hydrometerological variables at annual, daily and hourly timesteps. Quantification of system wide risks then enables detailed investigation of the effects of hydrometeorological risk on a major system participant. The third part of this dissertation selects the high-profile power utility Pacific Gas and Electric (PG&E) and investigates the effects of rapid retail load defection on the utility’s financial exposure to hydrometerological risk. The collective results provide novel information that can contribute to the development of improved weather risk management strategies in the electric power sector.Doctor of Philosoph

Financial Losses from Generation Oversupply in Hydropower-Dominated System with Growing Wind Capacity

The rapid expansion of intermittent forms of renewable energy makes it difficult to balance electricity supply and demand at the grid-scale. While much attention has focused on the risk of shortfall, oversupply (supply > demand) also presents challenges that can lead to financial losses by utilities and/or consumers when renewable energy is “curtailed”. Few studies have addressed this problem, so an integrated hydro-economic systems model is developed for the Columbia Basin to assess the frequency and severity of financial losses arising from oversupply due to wind power generation, particularly during wet years in which hydropower is abundant. Losses are evaluated under several future scenarios including increased wind capacity, changing natural gas prices and greater transmission capacity for moving excess electricity to export markets. Results indicate that oversupply losses increase as a function of installed wind capacity, but the cost of additional transmission capacity is substantially more than the resulting reduction in oversupply losses and is therefore difficult to justify.Master of Scienc

Single-crystal organometallic perovskite optical fibers

Semiconductors in their optical-fiber forms are desirable. Single-crystal organometallic halide perovskites have attractive optoelectronic properties and therefore are suitable fiber-optic platforms. However, single-crystal organometallic perovskite optical fibers have not been reported before due to the challenge of one-directional single-crystal growth in solution. Here, we report a solution-processed approach to continuously grow single-crystal organometallic perovskite optical fibers with controllable diameters and lengths. For single-crystal MAPbBr3 (MA = CH3NH3+) perovskite optical fiber made using our method, it demonstrates low transmission losses (<0.7 dB/cm), mechanical flexibilities (a bending radius down to 3.5 mm), and mechanical deformation-tunable photoluminescence in organometallic perovskites. Moreover, the light confinement provided by our organometallic perovskite optical fibers leads to three-photon absorption (3PA), in contrast with 2PA in bulk single crystals under the same experimental conditions. The single-crystal organometallic perovskite optical fibers have the potential in future optoelectronic applications

Comparative Agreement Analysis of Differences in 1,5-Anhydroglucitol, Glycated Albumin, and Glycated Hemoglobin A1c Levels between Fasting and Postprandial States in Steamed Bread Meal Test

Background. Our previous study indicated that serum 1,5-anhydroglucitol (1,5-AG) levels slightly increased after a glucose load; therefore, this study was conducted to explore short-term changes in 1,5-AG levels after a steamed bread meal test (SBMT) and compare the agreement of 1,5-AG, glycated albumin (GA), and glycated hemoglobin A1c (HbA1c) levels between fasting and postprandial states after an SBMT. Methods. 104 participants were recruited and underwent a 100 g SBMT. Fasting, 30 min, and 120 min of 1,5-AG, GA, and HbA1c were measured. Results. Levels of 1,5-AG slightly increased from 30 to 120 min after an SBMT (P0.05), and Bland-Altman difference plot showed that 100% of data points for HbA1c30 and HbA1c120 fell within the limits of agreement; 94.2%, 96.2%, 95.2%, and 95.2% of data points for 1,5-AG30, 1,5-AG120, GA30, and GA120 fell within the limits of agreement, respectively. Conclusion. Agreement analyses indicated good stability of 1,5-AG, GA, and HbA1c levels after the SBMT. HbA1c had an optimal stability, which was superior to that of GA or 1,5-AG

Metabonomics Combined with UPLC-MS Chemical Profile for Discovery of Antidepressant Ingredients of a Traditional Chinese Medicines Formula, Chaihu-Shu-Gan-San

This study proposed a new strategy for uncovering the active chemical constituents of a traditional Chinese medicines (TCMs) formula, Chaihu-Shu-Gan-San (CSGS). Metabonomics and chemical profile were integrated in combination with the multivariate statistical analysis (MVA) to discover the chemical constituents which contribute to the antidepressant effect of CSGS. Based upon the difference between CSGS and QZ (CSGS without Zhi-Qiao) extracts in the chemical profiles and the regulations of metabolic disturbances induced by CUMS, synephrine, naringin, hesperidin, and neohesperidin were recognized as the active constituents of CSGS from Zhi-qiao responsible for those missing regulations of CSGS when Zhi-Qiao was subtracted from the whole formula. They participated in the regulations of the deviated metabolites 2–4, 10–14, and 22–25, involved in metabolic pathways of ketone bodies synthesis, phenylalanine, tyrosine and tryptophan biosynthesis, valine, aspartate, glutamate metabolism, and glycolysis/gluconeogenesis. Furthermore, the assay of MAO-A activity confirmed the potential antidepressant effect of naringin and its active sites on the MAO-A was inferred by molecular docking study. The integration of metabonomics and chemical profile was proved to be a useful strategy for uncovering what the active chemical constituents in TCM formula are and how they make contributions for the efficacy of the formula

“Be a Pattern for the World”: The Development of a Dark Patterns Detection Tool to Prevent Online User Loss

Dark Patterns are designed to trick users into sharing more information or spending more money than they had intended to do, by configuring online interactions to confuse or add pressure to the users. They are highly varied in their form, and are therefore difficult to classify and detect. Therefore, this research is designed to develop a framework for the automated detection of potential instances of web-based dark patterns, and from there to develop a software tool that will provide a highly useful defensive tool that helps detect and highlight these patterns

Acidochromic organic photovoltaic integrated device

Tremendous efforts have been devoted to boosting the power conversion efficiency (PCE) of organic solar cells (OSCs) via the introduction of cathode interlayers (CILs). However, CIL materials have limited diversity and the development of multifunctional devices is largely neglected. Herein, an acidochromic organic photovoltaic integrated device is firstly proposed by introducing an acid-sensitive stimulating-reaction organic molecule as both the CIL of OSCs and the sensor of monitoring environmental acidity. The oxazolidine unit of acidochromic molecule can form a ring-opening structure after acid treatment, resulting in the remarkable color change with the direct reflection of pH value of ecological environment. The additive-free PM6:Y6 OSCs using the acidochromic molecule as the CIL achieve an excellent PCE of above 15.29 %, which is 47 % higher than that of the control device. The PCE can even maintain above 92 % after treating CIL with various strong acids (pH = 1). Moreover, the color of acidified films and the degraded performance of acidified OSCs can be easily restored by alkaline treatment. The successful application of CIL in other highly efficient photovoltaic systems proves its good universality. This work triggers the promising application of acidochromic molecules in solar cells as CIL with the additional function of recognition of acid environment