Large Scale Integration of Electric Vehicles into the Power Grid and Its Potential Effects on Power System Reliability

In this thesis, the potential effects of large scale integration of electric vehicles into the power grid are discussed in both the beneficial and detrimental aspects. The literature review gives a comprehensive introduction about the existing smart charging algorithms. According to the system structure and market mechanism, the smart charging algorithms can be divided into centralized and distributed method. With the knowledge of driving patterns and charging characteristics of electric vehicles, both the centralized and decentralized smart charging algorithms are studied in this research. Based on the smart charging pricing and sequential price update mechanism, a multi-agent based distributed smart charging algorithm is used in this research to flatten the load curve and therefore mitigate the potential detrimental effects caused by uncoordinated charging. Each EV agent has some extent of intelligence to solve its own charging scheduling problem. The optimization method used in this research is the binary hybrid GSA-PSO algorithm, which combines the merits of particle swarm optimization (PSO) and gravitational search algorithm (GSA), and has very good exploration and exploitation abilities. A V2G enabled centralized smart charging algorithm is also introduced in this thesis, each EV can earn revenues by discharging power into the grid. The dominant search matrix is used to resolve the \u27\u27curse of dimensionality\u27\u27 problem existing in the centralized optimization problems. Numerical case studies show both the distributed and V2G enabled smart charging algorithms can effectively transfer the charging load from the peak load period to the load valley hours. Because of the limited integration ratio of electric vehicles, most power system reliability methods do not evaluate the charging load of EVs separately in their analytical procedures. However, with a fast increasing integration level, the potential effects of large scale integration of EVs on the power system reliability should be comprehensively evaluated. The effects of EV charging on power system reliability in the planning phase is analyzed in this research based on the RBTS. The results show the uncontrolled charging will deteriorate the reliability level while the smart charging can effectively decrease the detrimental effect. The potential application of aggregated EV providing operating reserve to the grid as a kind of ancillary service is also discussed, and the related effects on power system reliability in operating phase are calculated using the modified PJM method. The case study shows the unit commitment risk of the system can decrease to a very low level with the additional operating reserve capacity provided by aggregated EVs, which can not only improve the system\u27s reliability level but also save the cost

Normalization of large-scale behavioural data collected from zebrafish

Many contemporary neuroscience experiments utilize high-throughput approaches to simultaneously collect behavioural data from many animals. The resulting data are often complex in structure and are subjected to systematic biases, which require new approaches for analysis and normalization. This study addressed the normalization need by establishing an approach based on linear-regression modeling. The model was established using a dataset of visual motor response (VMR) obtained from several strains of wild-type (WT) zebrafish collected at multiple stages of development. The VMR is a locomotor response triggered by drastic light change, and is commonly measured repeatedly from multiple larvae arrayed in 96-well plates. This assay is subjected to several systematic variations. For example, the light emitted by the machine varies slightly from well to well. In addition to the light-intensity variation, biological replication also created batch-batch variation. These systematic variations may result in differences in the VMR and must be normalized. Our normalization approach explicitly modeled the effect of these systematic variations on VMR. It also normalized the activity profiles of different conditions to a common baseline. Our approach is versatile, as it can incorporate different normalization needs as separate factors. The versatility was demonstrated by an integrated normalization of three factors: light-intensity variation, batch-batch variation and baseline. After normalization, new biological insights were revealed from the data. For example, we found larvae of TL strain at 6 days post-fertilization (dpf) responded to light onset much stronger than the 9-dpf larvae, whereas previous analysis without normalization shows that their responses were relatively comparable. By removing systematic variations, our model-based normalization can facilitate downstream statistical comparisons and aid detecting true biological differences in high-throughput studies of neurobehaviour

Expression profiling of the retina of pde6c, a zebrafish model of retinal degeneration

Retinal degeneration often affects the whole retina even though the disease-causing gene is specifically expressed in the light-sensitive photoreceptors. The molecular basis of the retinal defect can potentially be determined by gene-expression profiling of the whole retina. In this study, we measured the gene-expression profile of retinas microdissected from a zebrafish pde6cw59 (pde6c) mutant. This retinal-degeneration model not only displays cone degeneration caused by a cone-specific mutation, but also other secondary cellular changes starting from 4 days postfertilization (dpf). To capture the underlying molecular changes, we subjected pde6c and wild-type (WT) retinas at 5 dpf/ 120 h postfertilization (hpf) to RNA sequencing (RNA-Seq) on the Illumina HiSeq 2,000 platform. We also validated the RNA-Seq results by Reverse Transcription Quantitative Polymerase Chain Reaction (RT-qPCR) of seven phototransduction genes. Our analyses indicate that the RNA-Seq dataset was of high quality, and effectively captured the molecular changes in the whole pde6c retina. This dataset will facilitate the characterization of the molecular defects in the pde6c retina at the initial stage of retinal degeneration

Heat extraction capacity and its attenuation of deep borehole heat exchanger array

A model is proposed to analyze the heat transfer of deep borehole heat exchanger (DBHE)arrays. Based on this, a dimension reduction algorithm is proposed for the numerical simulation of heat transfer of DBHE arrays, which can improve calculation speed by several orders of magnitude compared with that by the CFD software. An index of heat extraction capacity (HECI) is adopted to evaluate the heat extraction capacity of DBHE arrays. The influence of borehole spacing, operation time, annual heating duration, terrestrial heat flow rate, borehole depth, soil thermal parameters, pipe diameter and circulating fluid flow rate on DBHE array heat extraction capacity and its attenuation are analyzed. The results show that the borehole spacing, operation time, and annual heating duration all have apparent influence on DBHE array heat extraction capacity and its attenuation rate, while the others only have apparent influence on the heat extraction capacity. According to the calculation results, when the DBHE arrays have a service lifetime of 20–50 years, the recommended borehole spacing range is 40–70 m

Media framing and public support for China’s social credit system: An experimental study

Although China’s social credit system (SCS) is widely portrayed by Western media as repressive surveillance, recent studies show that it receives high levels of support among Chinese citizens. Previous research suggests that people support the SCS because they lack knowledge about the system. This study further examines the roles of media framing (Western vs Chinese framing) and monitored behaviors (financial vs social behaviors). The results from a survey experiment conducted in China (N = 1600) demonstrate that when exposed to Western framing, public support for the SCS is lower, but only when participants are informed that the SCS monitors social behavior. By contrast, when people are told that the SCS focuses on financial behavior, Western framing exposure is not associated with low levels of public support. The findings suggest that an expansion to social domains and exposure to Western media framing will likely result in decreased support for the system