M.Ing. / Along with the increased use of power-electronic devices, there has been an increase in the magnitudes of distorted currents. Much of the power-theory in use today was devised many decades ago, mostly for AC-systems with clean sinusoidal voltages and currents. Modem loads are more often no longer mostly linear. Against the background of a study in the basic mathematics underlying AC power theory, a few techniques concerned with per-frequency power were examined. In addition certain concerns surrounding the use of correlation indexes for the purposes of load identification were also examined.

Scaling is a major problem in cooling water circuits as it reduces water flow and therefore affects the efficiency of the circuit. The natural organic matter has been suggested in earlier studies to limit the formation of calcium carbonate scaling by complexing the calcium ion. It was therefore the aim of this study to characterize the natural organic matter in the cooling water circuits at Lethabo power station (Vereeniging) and to investigate its potential to complex with calcium. The cooling water and raw water samples were comprehensively analyzed for major metal ions, anions and dissolved organic carbon using AAS, ICP-OES, IC and TOC analyzer and the results entered into MINTEQA2 speciation program to determine the precipitation potential of aragonite and calcite in the water samples. The natural organic matter from the cooling water and raw water were isolated initially through the cross-flow ultrafiltration using a polysulfone membrane with a molecular weight cut-off of 45 kDa. The collected isolates were characterized by ultraviolet-visible spectrophotometer, Fourier transform-infrared spectroscopy and (carbon, hydrogen and nitrogen) elemental analysis. The natural organic matter was also fractionated on ultrafiltration stirred cells using membranes with molecular weight cut-off of 1 kDa, 10 kDa and 100 kDa and then characterized using high performance size-exclusion chromatography. The isolated fractions were also titrated with sodium hydroxide and with calcium chloride to determine the amounts of carboxylic and phenolic groups available for complexation and the extent of the complexation of the fractions with calcium respectively. The speciation results from MINTEQA2 indicated that the raw water had a potential to be corrosive and the cooling water had a potential to scale. Higher concentrations of the natural organic matter were detected in the permeate from the cross-flow ultrafiltration process which suggested that it had predominantly a low molecular weight fraction. This low molecular weight fraction was further confirmed by the results from the high performance size-exclusion chromatography analysis of the fractions obtained from the fractionation process using ultrafiltration stirred cells. The specific ultraviolet absorbance and ratios of 465 to 656 nm absorbances results indicated that the organic compounds were mostly aliphatic in character. Titration of the concentrated organic isolates with sodium hydroxide solution revealed that the fractions had a high content of titratable acidic groups and titrating with calcium chloride showed that there is considerable complexation with calcium to affect calcium carbonate precipitation. / Dr. M. Shumane

No description available.

No description available.

No description available.

A plan for integrating modeling techniques and improving hydroelectric plant performance is presented. The plan begins with defining and establishing basic plant modeling parameters from the physical plant description. Guidelines for forming linear or nonlinear mathematical models are developed and the plan culminates in the determination of settings for P-I-D control which achieve optimum plant performance. Mathematical models are developed for the hydroelectric plant components -- the penstock, the hydraulic turbine (specifically a Francis turbine), the generator with its connected electrical system, and the control system. A unique method for characterizing turbine performance from a hill diagram is presented. Stability regions for linear models are determined and control settings which result in optimum plant performance are established. Settings associated with high derivative gains are indicated as giving optimum performance when a linear plant model is used. Nonlinear simulations at various operating conditions reveal that less lively gains must be used for the required gate motion to be achievable. For the representative plant model studied, the optimum governor settings resulted in a 7 percent improvement over other recommended P-I-D settings while satisfying gate speed constraints which the other recommended settings violated. The benefit of this work is in an improved ability to develop and utilize appropriate mathematical models for a hydroelectric plant and in the determination of control settings which improve plant performance. / Ph. D.

A newly-developed technique for short-term load forecasting is generalized. The algorithm combines features from knowledge-based and statistical techniques. The technique is based on a generalized model for the weather-load relationship, which makes it site independent. Weather variables are investigated, and their relative effect on the load is reported. That effect is modeled via a set of parameters and rules that constitute the rule based technique. This technique is very close to the intuitive judgmental approach an operator would use to make his guess of the load. That is why it provides a systematic way for operator intervention if necessary. This property makes the technique especially suitable for application in conjunction with demand side management (DSM) programs. Moreover, the algorithm uses pairwise comparison to quantify the categorical variables, and then utilizes regression to obtain the least-square estimation of the load. Because it uses the pairwise comparison technique, it is fairly robust. Since the forecast does not depend on any preset model, the technique is inherently updatable. A generalized version of the technique has been tested using data from four different sites in Virginia, Massachusetts, Florida and Washington. The average absolute weekday forecast errors range from 1.30% to 3.10% over all four seasons in a year. Error distributions show that the errors are 5% or less around 91 % of the time. / Master of Science

Thesis (M.S.)--Ohio University, June, 2008. / Title from PDF t.p. Includes bibliographical references.

Thesis: M.S., Massachusetts Institute of Technology, Department of Mechanical Engineering, 1978 / Includes bibliographical references. / M.S. / M.S. Massachusetts Institute of Technology, Department of Mechanical Engineering

Thesis (M.B.A.)--University of Hong Kong, 1983.