HOUSEHOLD SOLAR POWER SYSTEM

Photovoltaic power has become one of the most popular research area in new energy field. In this report, the case of household solar power system is presented. Based on the Matlab environment, the simulation is built by using Simulink and SimPowerSystem. There are four parts in a household solar system, solar cell, MPPT system, battery and power consumer. Solar cell and MPPT system are been studied and analyzed individually. The system with MPPT generates 30% more energy than the system without MPPT. After simulating the household system, it is can be seen that the power which generated by the system is 40.392 kWh per sunny day. By combining the power generated by the system and the price of the electric power, 8.42 years are need for the system to achieve a balance of income and expenditure when weather condition is considered.

Maximum principle preserving high order schemes for convection-dominated diffusion equations

The maximum principle is an important property of solutions to PDE. Correspondingly, it's of great interest for people to design a high order numerical scheme solving PDE with this property maintained. In this thesis, our particular interest is solving convection-dominated diffusion equation. We first review a nonconventional maximum principle preserving(MPP) high order finite volume(FV) WENO scheme, and then propose a new parametrized MPP high order finite difference(FD) WENO framework, which is generalized from the one solving hyperbolic conservation laws. A formal analysis is presented to show that a third order finite difference scheme with this parametrized MPP flux limiters maintains the third order accuracy without extra CFL constraint when the low order monotone flux is chosen appropriately. Numerical tests in both one and two dimensional cases are performed on the simulation of the incompressible Navier-Stokes equations in vorticity stream-function formulation and several other problems to show the effectiveness of the proposed method.

A TWO-STAGE MICROBIAL FUEL CELL SYSTEM TO CONVERT SOLID ORGANIC WASTE TO ELECTRICITY

Microbial fuel cell (MFC) research has focused mostly on producing electricity using soluble organic and inorganic substrates. This study focused on converting solid organic waste into electricity using a two-stage MFC process. In the first stage, a hydrolysis reactor produced soluble organic substrates from solid organic waste. The soluble substrates from the hydrolysis reactor were pumped to the second stage reactor: a continuous-flow, air-cathode MFC. Maximum power output (Pmax) of the MFC was 296 mW/m3 at a current density of 25.4 mA/m2 while being fed only leachate from the first stage reactor. Addition of phosphate buffer increased Pmax to 1,470 mW/m3 (89.4 mA/m2), although this result could not be duplicated with repeated polarization testing. The minimum internal resistance achieved was 77 Omega with leachate feed and 17 Omega with phosphate buffer. The low coulombic efficiency (

Application of MFBD Algorithms to Image Reconstruction Under Anisoplanatic Conditions

All optical systems that operate in or through the atmosphere suffer from turbulence induced image blur. Both military and civilian surveillance, gun-sighting, and target identification systems are interested in terrestrial imaging over very long horizontal paths, but atmospheric turbulence can blur the resulting images beyond usefulness. My dissertation explores the performance of a multi-frame-blind-deconvolution technique applied under anisoplanatic conditions for both Gaussian and Poisson noise model assumptions. The technique is evaluated for use in reconstructing images of scenes corrupted by turbulence in long horizontal-path imaging scenarios and compared to other speckle imaging techniques. Performance is evaluated via the reconstruction of a common object from three sets of simulated turbulence degraded imagery representing low, moderate and severe turbulence conditions. Each set consisted of 1000 simulated, turbulence degraded images. The MSE performance of the estimator is evaluated as a function of the number of images, and the number of Zernike polynomial terms used to characterize the point spread function. I will compare the mean-square-error (MSE) performance of speckle imaging methods and a maximum-likelihood, multi-frame blind deconvolution (MFBD) method applied to long-path horizontal imaging scenarios. Both methods are used to reconstruct a scene from simulated imagery featuring anisoplanatic turbulence induced aberrations. This comparison is performed over three sets of 1000 simulated images each for low, moderate and severe turbulence-induced image degradation. The comparison shows that speckle-imaging techniques reduce the MSE 46 percent, 42 percent and 47 percent on average for low, moderate, and severe cases, respectively using 15 input frames under daytime conditions and moderate frame rates. Similarly, the MFBD method provides, 40 percent, 29 percent, and 36 percent improvements in MSE on average under the same conditions. The comparison is repeated under low light conditions (less than 100 photons per pixel) where improvements of 39 percent, 29 percent and 27 percent are available using speckle imaging methods and 25 input frames and 38 percent, 34 percent and 33 percent respectively for the MFBD method and 150 input frames. The MFBD estimator is applied to three sets of field data and the results presented. Finally, a combined Bispectrum-MFBD Hybrid estimator is proposed and investigated. This technique consistently provides a lower MSE and smaller variance in the estimate under all three simulated turbulence conditions.