Connecting two wind turbine generators to the grid using only one three level NPC inverter

This paper explores the possibility of connecting two Wind Turbine Generators (WTG) to the grid using a single three level inverter. In the proposed system the rectified output of one WTG is connected across the upper dc-link capacitor of a standard diode clamped three level inverter. Similarly the rectified output of the other WTG is connected across the lower capacitor. This particular combination has several advantages such as, direct connection to the grid, reduced parts count, improved reliability and high power capacity. However, the major problem in the proposed system is the imminent imbalance of dc-link voltages. Under such conditions conventional modulation methods fail to produce desired voltage and current waveforms. A detailed analysis on this issue and a novel space vector modulation method, as the solution, are proposed in this paper. To track the Maximum power point of each WTG a power sharing algorithm is proposed. Simulation results are presented to attest the efficacy of the proposed system.

Dual inverter based battery energy storage system for grid connected photovoltaic systems

This paper explores a new breed of energy storage system interfacing for grid connected photovoltaic (PV) systems. The proposed system uses the popular dual inverter topology in which one inverter is supplied by a PV cell array and the other by a Battery Energy Storage System (BESS). The resulting conversion structure is controlled in a way that both demand matching and maximum power point tracking of the PV cell array are performed simultaneously. This dual inverter topology can produces 2, 3, 4 and 5 level inverter voltage waveforms at the dc-link voltage ratios of 0:1, 1:1, 2:1 and 3:2 respectively. Since the output voltage of the PV cell array and the battery are uncorrelated and dynamically change, the resulting dc-link voltage ratio can take non-integer values as well. These noninteger dc-link voltage ratios produce unevenly distributed space vectors. Therefore, the main issue with the proposed system is the generation of undistorted current even in the presence of unevenly distributed and dynamically changing space vectors. A modified space vector modulation method is proposed in this paper to address this issue and its efficacy is proved by simulation results. The ability of the proposed system to act as an active power source is also verified.

Z-source converter based grid-interface for variable-speed permanent magnet wind turbine generators

A Z-source inverter based grid-interface for a variable-speed wind turbine connected to a permanent magnet synchronous generator is proposed. A control system is designed to harvest maximum wind energy under varied wind conditions with the use of the permanent magnet synchronous generator, diode-rectifier and Z-source inverter. Control systems for speed regulation of the generator and for DC- and AC- sides of the Z-source inverter are investigated using computer simulations and laboratory experiments. Simulation and experimental results verify the efficacy of the proposed approach.

Bayesian hierarchical models for analysing spatial point-based data at a grid level: A comparison of approaches

Spatial data are now prevalent in a wide range of fields including environmental and health science. This has led to the development of a range of approaches for analysing patterns in these data. In this paper, we compare several Bayesian hierarchical models for analysing point-based data based on the discretization of the study region, resulting in grid-based spatial data. The approaches considered include two parametric models and a semiparametric model. We highlight the methodology and computation for each approach. Two simulation studies are undertaken to compare the performance of these models for various structures of simulated point-based data which resemble environmental data. A case study of a real dataset is also conducted to demonstrate a practical application of the modelling approaches. Goodness-of-fit statistics are computed to compare estimates of the intensity functions. The deviance information criterion is also considered as an alternative model evaluation criterion. The results suggest that the adaptive Gaussian Markov random field model performs well for highly sparse point-based data where there are large variations or clustering across the space; whereas the discretized log Gaussian Cox process produces good fit in dense and clustered point-based data. One should generally consider the nature and structure of the point-based data in order to choose the appropriate method in modelling a discretized spatial point-based data.

Numerical simulation of micro-scale morphological changes of plant food materials during drying - a meshfree approach

This thesis developed a high preforming alternative numerical technique to investigate microscale morphological changes of plant food materials during drying. The technique is based on a novel meshfree method, and is more capable of modeling large deformations of multiphase problem domains, when compared with conventional grid-based numerical modeling techniques. The developed cellular model can effectively replicate dried tissue morphological changes such as shrinkage and cell wall wrinkling, as influenced by moisture reduction and turgor loss.

Numerical optimization of soft-mold aided co-curing process of advanced grid-stiffened composite structures

The co-curing process for advanced grid-stiffened (AGS) composite structure is a promising manufacturing process, which could reduce the manufacturing cost, augment the advantages and improve the performance of AGS composite structure. An improved method named soft-mold aided co-curing process which replaces the expansion molds by a whole rubber mold is adopted in this paper. This co-curing process is capable to co-cure a typical AGS composite structure with the manufacturer’s recommended cure cycle (MRCC). Numerical models are developed to evaluate the variation of temperature and the degree of cure in AGS composite structure during the soft-mold aided co-curing process. The simulation results were validated by experimental results obtained from embedded temperature sensors. Based on the validated modeling framework, the cycle of cure can be optimized by reducing more than half the time of MRCC while obtaining a reliable degree of cure. The shape and size effects of AGS composite structure on the distribution of temperature and degree of cure are also investigated to provide insights for the optimization of soft-mold aided co-curing process.

Modeling dynamic demand response using Monte Carlo simulation and interval mathematics for boundary estimation

With the rapid development of various technologies and applications in smart grid implementation, demand response has attracted growing research interests because of its potentials in enhancing power grid reliability with reduced system operation costs. This paper presents a new demand response model with elastic economic dispatch in a locational marginal pricing market. It models system economic dispatch as a feedback control process, and introduces a flexible and adjustable load cost as a controlled signal to adjust demand response. Compared with the conventional “one time use” static load dispatch model, this dynamic feedback demand response model may adjust the load to a desired level in a finite number of time steps and a proof of convergence is provided. In addition, Monte Carlo simulation and boundary calculation using interval mathematics are applied for describing uncertainty of end-user's response to an independent system operator's expected dispatch. A numerical analysis based on the modified Pennsylvania-Jersey-Maryland power pool five-bus system is introduced for simulation and the results verify the effectiveness of the proposed model. System operators may use the proposed model to obtain insights in demand response processes for their decision-making regarding system load levels and operation conditions.