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This paper analyses the impact of tie-lines connecting different areas of power system and the location of wind farms on the small signal stability of a power system. The analysis is conducted using Monte Carlo simulation via modal analysis. The random samples are generated from two-parameter Weibull distribution to obtain possible representation of wind speed needed for the generation of wind power using Latin hypercube sampling techniques. The sampling technique allows the usage of a small sample size, which helps in reducing the simulation cost without jeopardising the accuracy of the result. Different scenarios are created and the oscillatory modes are calculated for different operating condition. The changes in modal characteristic of the system due to different operating conditions are evaluated by observing the movement on the complex plane. The results of the modal analysis for each scenario are validated using time domain simulation. Some of the key results show that wind power can have either positive or negative impact on the oscillation of a power system depending on the location in which it is integrated into the power system. It is also found out that strengthening the weak tie-lines can greatly improve the inter-area mode. This paper is useful in the planning stage of wind power projects.

In the food and beverage industry, where growing, processing, packaging, distribution, storage, preparation, serving and disposing of food is the order of the day; energy consumption becomes an important input. Various energy models have been developed since the early 1970s, the period when energy caught the attention of policymakers due to the sudden price increase. Among the models are the index decomposition analysis (IDA), artificial neural network (ANN) and data envelopment analysis (DEA). The purpose of this study is to combine the strengths of these models, i.e., IDA, ANN and DEA, to allow biases in one model to offset biases in the other, so as to examine the effectiveness of energy management policies in a particular food and beverage industry. The integrated model applied to the food and beverage revealed that approximately 11% of energy consumed could be saved.

In view of the close association between energy and economic growth, South Africa's aspirations for higher growth, more energy is required; formulating a long-term economic development plan and implementing an energy strategy for a country /industry necessitates establishing the correct relationship between energy and the economy. As insufficient energy or a lack thereof is reported to be a major cause of social and economic poverty, it is very important to select a model to forecast the consumption of energy reasonably accurately. This study presents techniques based on the development of multilayer perceptron (MLP) and radial basis function (RBF) of artificial neural network (ANN) models, for calculating the energy consumption of South Africa's industrial sector between 1993 and 2000. The approach examines the energy consumption in relation to the gross domestic product. The results indicate a strong agreement between model predictions and observed values, since the mean absolute percentage error is below 5%. When performance indices are compared, the RBF-based model is a more accurate predictor than the MLP model.

Modelling and Analysis of Squirrel Cage Induction Motor with Leading Reactive Power Injection

Understanding and minimizing loss are the main objectives of seeking solutions to the problems of stray loss in induction machines. This thesis contributes towards this objective by addressing the various problems of stray load loss. These problems include the questions of definition, origin, components, and effects; theoretical and experimental means of evaluation; and loss reduction. Insights into these problems are achieved through a comprehensive review of the state of the art of the subject. We have established that some commonly used terminologies in the subject area formed major obstacles to progress in definition. A conceptually simple and general theory of squirrel cage induction machines is presented. The theory results in a set of linear periodic differential equations, which has an infinite number of possible solutions. A suitable solution procedure is developed. Means for accounting for slot openings and saturation are developed. These have enabled various field waveforms in a practical machine to be generated and analyzed. The analysis produced insights into the interactions of harmonics and how harmonics contribute to stray load losses. Through this, an approximate means of separating a saturated non-sinusoidal waveform of an air gap flux density waveform into its fundamental, saturation, and other space harmonics is developed. An expression for determining the machine torque is derived. This torque expression, the ideas for manipulating and analyzing the field waveforms, and the presented theory are structured into an algorithm, modeling the behaviours of squirrel cage induction machines. The algorithm enabled the torque-speed characteristic of a practical machine to be predicted. The predicted characteristic is compared with that measured by means of accelerometer. The fact that it compares very well validates the theory and the developed model. The new steady state model has several advantages, including its easy application to the study and the evaluation of stray load losses. A brief study of how harmonics influence the developed torque is also conducted using the new model. Two theoretical methods are developed for predicting stray load loss at the design, manufacturing, or utilization stage of a machine. These methods, which employ the developed model, are applied to a practical machine. The predicted stray losses are compared with the measured, and that predicted using the nominal assignation technique. This draws attention to the need for experimental investigation of the subject. Consequently, two experiments, calorimetric method and novel experiment to study inter-bar current problem, are developed. Due to technical and economic problems, however, their implementation are not yet completed. Doctor of Philosophy (PhD)