Modeling and dynamic stability of distributed generations

The objective of this dissertation is to develop dynamic models for distributed generations (DG), to investigate their impacts on dynamic stability of power distribution systems, and to design controllers for DGs to improve the dynamic stability of the integrated power distribution system.;A two-year distributed generation (DG) project at West Virginia University (WVU) evaluated the impact of various DG sources on actual distribution systems by performing computer simulations. The data is supplied by two regional electric utilities of two actual distribution systems each. In this project several important issues were investigated, including the availability of simulation tools and impacts of DGs connected to a distribution line under a variety of line operating conditions. Based on this preliminary research the further most interesting topics for continued research were raised.;The continued research has focused on deeper investigation, such as, modeling DG sources, evaluating their interaction and impacts, and improving the dynamic stability of the integrated power distribution system. Four specific DGs are studied in this dissertation: fuel cell power plant, wind turbine induction generator, gas turbine synchronous generator and diesel engine synchronous generator.;A full-order synchronous generator model represents the generator models of gas turbine generator and diesel engine generator. A simplified gas turbine model has been chosen to be implemented. A practical diesel engine for emergency use is modeled. The generator model of wind turbine induction generator is represented by a full-order induction generator. The rated power operating regime is considered for impacts evaluations and controller design. Two types of fuel cell models are developed. The first one is a model of already operational phosphoric acid fuel cell (PAFC) obtained through data fitting and the second one is dynamic model of solid oxide fuel cell (SOFC). Since fuel cells are connected to the electric power network via inverters, an inverter model has been developed.;Multi-DG controls are investigated in this dissertation. One DG control is fuel cell control, the other one is wind-turbine control. The control of fuel cell (SOFC) plant is through the inverter to adjust active power injection to the network during the transient time. The control of wind turbine generator is through the parallel connected SVC by adjusting reactive power injection to the system. Both control schemes are centralized.;Linear analysis methodologies are utilized in designing the controller. In the fuel cell control design, two pairs of critical modes are screened out using eigenvalue analysis. The participation factors of DGs with respect to the modes are calculated. Two specific lead-lag compensation units are designed to damp each mode separately. The gains of the two compensation units were then obtained via optimal control methodology. In wind turbine DG control design procedure, three rotor speed deviations are used as input signals while the controller outputs are the firing angle for the SVC and the pitch angle for the wind-turbine DG. An output feedback controller is designed. The dynamic load characteristic is also considered by modeling it as a structured uncertainty. mu-analysis is used to evaluate the robust stability of the controllers with respect to the uncertain parameters in the dynamic loads. The IEEE-13 node radial feeder with existing gas turbine and diesel engine DGs is used as a test system to evaluate the multi-DG control. The simulation results demonstrate the effectiveness of the control strategies.;Coordinated operation of all the DGs is investigated. Simulation results show that good configurations within DGs along the system can improve the system stability. Furthermore, the fast acting SVC is very effective in improving damping. Among the DGs investigated in this research, the fuel cell plant control is the best choice for the coordinated operation.;Finally, the approach to model a complete three-phase power distribution system is implemented. The impact of the developed DGs models is evaluated on a three-phase unbalanced distribution system. The three-phase 13-node IEEE system with gas turbine and diesel engine DGs is simulated using MATLAB/Simulink\u27s Power System Blockset (PSB). In the simulation, a three-phase thyristor controlled braking resistor (TCBR) is connected to absorb the surplus energy when the system is subjected to a disturbance. The three-phase dynamic simulation demonstrates the effectiveness of the proposed strategy

Least Squares Estimation-Based Synchronous Generator Parameter Estimation Using PMU Data

In this paper, least square estimation (LSE)-based dynamic generator model parameter identification is investigated. Electromechanical dynamics related parameters such as inertia constant and primary frequency control droop for a synchronous generator are estimated using Phasor Measurement Unit (PMU) data obtained at the generator terminal bus. The key idea of applying LSE for dynamic parameter estimation is to have a discrete \underline{a}uto\underline{r}egression with e\underline{x}ogenous input (ARX) model. With an ARX model, a linear estimation problem can be formulated and the parameters of the ARX model can be found. This paper gives the detailed derivation of converting a generator model with primary frequency control into an ARX model. The generator parameters will be recovered from the estimated ARX model parameters afterwards. Two types of conversion methods are presented: zero-order hold (ZOH) method and Tustin method. Numerical results are presented to illustrate the proposed LSE application in dynamic system parameter identification using PMU data.Comment: 5 pages, 6 figures, accepted by IEEE PESGM 201

Exploring How Tourism Majors’ Perceived Professional Competence Influences Their Choice of Tourism Careers in China

With the rapid development of tourism in China, various economic sectors such as agriculture, sports, food and beverages, cultural heritage, and outdoor adventure have become integrated into the tourism industry. China\u27s tourism industry has changed and these changes now require tourism practitioners to adapt. Chinese universities must also adapt their tourism curriculum and educational practices to reflect changes in the tourism sector. Research suggests that university training programs should increase their emphasis on developing students’ professional competency and expand the range of competencies they address in their curriculum. At the same time, tourism enterprises in China are unable to recruit enough competent employees, resulting in a shortage of qualified workers. To improve the professional competence of tourism students in China, tourism education departments must respond to the needs of, and changes in, the tourism industry. The purpose of this two-phase, mixed-method exploratory design study is to identify the professional competencies that tourism experts in China believe tourism students must acquire, and examine the relationship between these competencies, tourism students’ perceptions of professional competence, and their intent to pursue a career in the tourism sector. The present study began with basic qualitative research in the form of interviews with Chinese tourism experts in China to identify the professional competencies that Chinese tourism students need. During the second stage of research, these results were incorporated into a written questionnaire that was distributed to approximately 800 tourism majors in China. Through the analysis of survey data, we examined the relationship between student demographics, their perceived professional competence, and their intent to pursue a career in the tourism sector. The study results indicate that the causal relationship between students\u27 perceived professional competence and students\u27 intention for a career in tourism is valid. These findings provide theoretical support for improving tourism students\u27 perceived professional competency. The results also suggest strategies to increase the percentage of tourism students who will choose to work in the tourism sector upon graduation

The Study of Protein Conformation in Solution Via Direct Sampling by Desorption Electrospray Ionization Mass Spectrometry

The direct sampling feature of liquid sample desorption electrospray ionization (DESI) allows the ionization of liquid samples without adding acids/organic solvents (i.e., without sample pretreatment). As a result, it provides a new approach for probing protein conformation in solution. In this study, it has been observed that native protein ions are generated from proteins in water by DESI. Interestingly, the intensities of the resulting protein ions appear to be higher than those generated by ESI of the proteins in water or in ammonium acetate. For protein solutions that already contain acids/organic solvents, DESI can be used to investigate the influences of these denaturants on protein conformations and the obtained results are in good agreement with spectroscopic data. In addition, online monitoring of protein conformational changes by DESI is feasible; for instance, heat-induced unfolding of ubiquitin can be traced with DESI in water without influences of organic solvents/acids. This DESI method provides a new alternative tool for the study of protein conformation in solution

ISPTM: an Iterative Search Algorithm for Systematic Identification of Post-translational Modifications from Complex Proteome Mixtures

Identifying protein post-translational modifications (PTMs) from tandem mass spectrometry data of complex proteome mixtures is a highly challenging task. Here we present a new strategy, named iterative search for identifying PTMs (ISPTM), for tackling this challenge. The ISPTM approach consists of a basic search with no variable modification, followed by iterative searches of many PTMs using a small number of them (usually two) in each search. The performance of the ISPTM approach was evaluated on mixtures of 70 synthetic peptides with known modifications, on an 18-protein standard mixture with unknown modifications and on real, complex biological samples of mouse nuclear matrix proteins with unknown modifications. ISPTM revealed that many chemical PTMs were introduced by urea and iodoacetamide during sample preparation and many biological PTMs, including dimethylation of arginine and lysine, were significantly activated by Adriamycin treatment in NM associated proteins. ISPTM increased the MS/MS spectral identification rate substantially, displayed significantly better sensitivity for systematic PTM identification than the conventional all-in-one search approach and offered PTM identification results that were complementary to InsPecT and MODa, both of which are established PTM identification algorithms. In summary, ISPTM is a new and powerful tool for unbiased identification of many different PTMs with high confidence from complex proteome mixtures

FABP4-mediated lipid droplet formation in Streptococcus uberis-infected macrophages supports host defence

Foamy macrophages containing prominent cytoplasmic lipid droplets (LDs) are found in a variety of infectious diseases. However, their role in Streptococcus uberis-induced mastitis is unknown. Herein, we report that S. uberis infection enhances the fatty acid synthesis pathway in macrophages, resulting in a sharp increase in LD levels, accompanied by a significantly enhanced inflammatory response. This process is mediated by the involvement of fatty acid binding protein 4 (FABP4), a subtype of the fatty acid-binding protein family that plays critical roles in metabolism and inflammation. In addition, FABP4 siRNA inhibitor cell models showed that the deposition of LDs decreased, and the mRNA expression of Tnf, Il1b and Il6 was significantly downregulated after gene silencing. As a result, the bacterial load in macrophages increased. Taken together, these data demonstrate that macrophage LD formation is a host-driven component of the immune response to S. uberis. FABP4 contributes to promoting inflammation via LDs, which should be considered a new target for drug development to treat infections