M.Ing. / Spoornet currently has a fleet of more than 1500 electric locomotives in service. The majority of electric locomotives are resistor controlled but there are many chopper as well as thyristor controlled locomotives which all incorporate direct current (dc) traction motors. In recent years Spoornet has also bought locomotives employing alternating current (ac) traction motors. Because locomotives are very expensive and the running costs are high it is important that these locomotives must be available and reliable. Most of the newer generation locomotives, which are the semiconductor controlled locomotives, must be in service for at least another 20 years. The availability and reliability are often influenced by delayed design problems as well as problems arising due to changes in the total system configuration. One way of solving these problems, or at least understanding them, is by employing computer simulations. The availability and reliability can also be improved by using new technologies which were not originally employed on the locomotives. By doing computer simulations the optimal solution can be obtained when introducing new technologies on the locomotive. A good example of this type of application within Spoornet is given in [6], where simulation models for high technology locomotives were developed which were suitable to be used in the assessment of electromagnetic compatibility between modern power electronic locomotives and the railway signaling system. However, these models are also suited to be used in other applications. These models make use of the ATP-EMTP simulation program.

A dissertation submitted to the Facaulty of Engineering and the Built Environment, University of the Witwatersrand in ful lment of the requirements of the degree of Master of science in Engineering September 2016 / Standalone microgrid studies are being done because an expansion of the existing utility grids to supply power to remote communities is not feasible. Standalone microgrids can be considered as one of the solutions for remote communities because power can be generated close to these communities and it minimizes cost related to power transmission. Renewable energy sources with large uctuations are frequently the source of power for these standalone microgrids. The uctuating nature of these renewable sources can often lead to frequent blackouts. This research is aimed at minimizing power uctuations using controllable energy storage systems. This MSc focuses on the analysis of the ramp rate and delay time requirements for controllable energy storage system used in standalone PV microgrids. Measured insolation data and recorded load demand data for typical domestic appliances are used in this study to analyze ramp rates present. The ramp rates are then used to determine the range of energy storage ramp rate and delay time required to maintain the microgrid voltage within the standardized range of 1pu 5%. From the recorded data it has been observed that PV power can be sampled from at least 1-second intervals without losing important information. The 1 second averaged ramp rates obtained from the insolation data measurements have been found to have the highest value of 0.12pu/sec. However, this ramp rate increases to 0.3pu/sec when the allowable microgrid voltage band is narrow (1pu 5%). These insolation ramp rates are very low compared to the ramp rates of typical loads that can be connected to a microgrid. This means that, if the energy storage system is speci ed to meet the load ramp rate requirements, it will be able to respond to the uctuating PV power. The results obtained from the simulations con rm that energy storage system ramp rate plays an important role in the stability of a standalone microgrid. The minimum allowable energy storage ramp rate was found to be 8.15pu/sec for load transients with a ramp time of 20ms. This value is 28 times the energy storage ramp rate required to cancel out insolation uctuations. This further con rms that energy storage system ramp rates must be speci ed using the load demand data. The maximum allowable delay time was also found to be 0.53s to maintain the microgrid voltage within the standardized range of 1pu 5%. This delay time is applicable when canceling out only the insolation uctuations. To cancel out load transient power uctuations, there should be no delay time. / MT2017

A project report submitted to the Faculty of Engineering, University of the Witwatersrand, in partial fulfilment of the requirements for the degree of Master of Science in Engineering. Johannesburg 1995. / Advances in digital computing technology make it possible to improve the design of the Man Machine Interface (MMI), SCADA and ALARM modules used in electrical utility control centres. to overcome the problem of control staff data overloading. A possible solution is proposed, based on-an explicit representation of a disturbed power system state in addition to quiescent conditions. The structure of modem SCADA, installations is analysed in terms of the computing power of full graphic workstations, the quantities of element data delivered to the control room and the capabilities of intelligent remote terminal units. This analysis indicates that existing designs for the presentation of SCADA data need to change to solve the data overloading-problem. The proposed philosophy moves the focus of attention from the element level up to the device level by grouping and dividing all elements into categories at the RTU and linking them to their parent device, Control staff are notified graphically on the one-line displays, next to the device in question, of the existence of abnormal elements by category. The element state details for the device are only displayed on demand, resulting in a 95% reduction of alarm text messages. Suggestions are made as to the software functions needed at tbe RTU and the workstation to assist with the display of system data. Lastly racommendations are offered to reduce maintenance by standardising and pre-ordering device element data. / AC2017

Thesis (Master of Engineering in Electrical Engineering)--Cape Peninsula University of Technology, 2018. / As the electric energy demand grows, there is a significant increase in the penetration of renewable generation (RG) in the existing electrical grid network. Interconnecting of renewable generation technologies to an existing distribution system has proven to provide various benefits such as meeting the growing load demand and its contribution to energy system decarbonisation, long-term energy security and expansion of energy access to new energy consumers in the developing urban and rural areas. However, the aim of this thesis is to conduct a study on the impacts of renewable generation on the power quality of electrical grid. Therefore, this work aims at assessing the potential effects of Distributed Generation (DG) on the operation of electric power system by modelling of harmonics and voltage distortion. With different types of renewable generation available at present, it is believed that some designs contribute significantly to electrical network’s Power Quality (PQ). After the analysis of harmonic currents (chapter 6 and 7 of this thesis) introduced by renewable generation technologies, their negative impact on the power quality of the grid is seen to be apparent at point of connection (POC) but only within controlled limits. Analytical method for modeling of harmonic interactions between the grid and aggregated distributed generation technologies are investigated using DIgSILENT Power Factory software and the results obtained are discussed.

This thesis proposes a Power Management Model (PMM) for optimization of several green power generation systems. A Photovoltaic/Fuel cell Hybrid Energy System (PFHES) consisting of solar cells, electrolyzer and fuel cell stack is utilized to meet a specific DC load bank for various applications. The Photovoltaic system is the primary power source to take advantage of renewable energy. The electrolyzer-fuel cell integration is used as a backup and as a hydrogen storage system with the different energy sources integrated through a DC link bus. An overall power management strategy is designed for the optimization of the power flows among the different energy sources. Extensive simulation experiments have been carried out to verify the system performance under PMM governing strategy. The simulation results indeed demonstrate the effectiveness of the proposed approach. / by Rosana Melendez. / Thesis (M.S.C.S.)--Florida Atlantic University, 2010. / Includes bibliography. / Electronic reproduction. Boca Raton, Fla., 2010. Mode of access: World Wide Web.

Uninterruptable Power Supply (UPS) systems have become essential to modern industries that require continuous power supply to manage critical operations. Since a failure of a single battery will affect the entire backup system, UPS systems providers must replace any battery before it runs dead. In this regard, automated monitoring tools are required to determine when a battery needs replacement. Nowadays, a primitive method for monitoring the battery backup system is being used for this task. This thesis presents a classification model that uses data mining cleansing and processing techniques to remove useless information from the data obtained from the sensors installed in the batteries in order to improve the quality of the data and determine at a given moment in time if a battery should be replaced or not. This prediction model will help UPS systems providers increase the efficiency of battery monitoring procedures. / Includes bibliography. / Thesis (M.S.)--Florida Atlantic University, 2013.

by Lo Kam Ming. / Thesis (M.Phil.)--Chinese University of Hong Kong, 1996. / Includes bibliographical references (leaves 107-111). / Chapter 1 --- Introduction --- p.7 / Chapter 1.1 --- The Goal --- p.8 / Chapter 1.2 --- The Work of the Thesis --- p.9 / Chapter 1.3 --- Layout of Thesis --- p.9 / Chapter 2 --- The Unit Commitment Problem --- p.11 / Chapter 2.1 --- What is UCP? --- p.11 / Chapter 2.1.1 --- Why is UCP difficult? --- p.12 / Chapter 2.1.2 --- Costs --- p.12 / Chapter 2.1.3 --- Constraints --- p.13 / Chapter 2.2 --- Mathematical Formulation --- p.15 / Chapter 2.3 --- Literature Review --- p.19 / Chapter 2.3.1 --- Exhaustive Enumeration --- p.19 / Chapter 2.3.2 --- Priority List --- p.20 / Chapter 2.3.3 --- Langragian Relaxation --- p.21 / Chapter 2.3.4 --- Neural Network --- p.21 / Chapter 2.3.5 --- Genetic Algorithms --- p.22 / Chapter 2.3.6 --- Dynamic Programming --- p.22 / Chapter 3 --- Genetic Algorithms --- p.24 / Chapter 3.1 --- Introduction --- p.24 / Chapter 3.1.1 --- Outline of Traditional GA --- p.25 / Chapter 3.2 --- Basic elements --- p.26 / Chapter 3.2.1 --- Coding --- p.26 / Chapter 3.2.2 --- Fitness Function --- p.26 / Chapter 3.2.3 --- Selection and Reproduction --- p.26 / Chapter 3.2.4 --- Mutation --- p.28 / Chapter 3.2.5 --- Replacement --- p.29 / Chapter 3.2.6 --- Epistasis --- p.29 / Chapter 3.2.7 --- A Simple Example --- p.30 / Chapter 3.3 --- Exploration vs Exploitation --- p.33 / Chapter 3.4 --- Constraints Handlings --- p.34 / Chapter 3.4.1 --- Penalty Function --- p.35 / Chapter 3.4.2 --- Proper Encoding --- p.36 / Chapter 3.4.3 --- Repair Algorithms --- p.36 / Chapter 4 --- Dynamic Programming --- p.37 / Chapter 4.1 --- Introduction --- p.37 / Chapter 4.1.1 --- Decomposition --- p.38 / Chapter 4.2 --- Mathematical Formulation --- p.43 / Chapter 4.3 --- A Simple Example --- p.44 / Chapter 5 --- DP Crossover Operator (DPX) --- p.50 / Chapter 5.1 --- Why DP is chosen as the crossover operator --- p.50 / Chapter 5.2 --- What is DPX? --- p.51 / Chapter 5.2.1 --- A Simple Example --- p.51 / Chapter 5.2.2 --- Mechanism of DPX --- p.58 / Chapter 5.3 --- Properties of DPX --- p.63 / Chapter 5.3.1 --- Number of parents --- p.63 / Chapter 5.3.2 --- Crossover Sites --- p.65 / Chapter 5.3.3 --- Perservation of Feasibility --- p.66 / Chapter 6 --- Implementation --- p.69 / Chapter 6.1 --- GA Construction --- p.69 / Chapter 6.1.1 --- Coding --- p.69 / Chapter 6.1.2 --- Fitness Function --- p.70 / Chapter 6.1.3 --- Selection --- p.72 / Chapter 6.1.4 --- Crossover --- p.76 / Chapter 6.1.5 --- Mutation Rate --- p.76 / Chapter 6.1.6 --- Replacement --- p.77 / Chapter 6.2 --- Algorithm --- p.77 / Chapter 6.3 --- Optimal Power Generations for Fuel Costs --- p.80 / Chapter 6.3.1 --- The Simple Scheduling Method --- p.80 / Chapter 7 --- Experimental Results --- p.84 / Chapter 7.1 --- Experiment Details --- p.84 / Chapter 7.2 --- Problem A --- p.86 / Chapter 7.2.1 --- Data Results --- p.86 / Chapter 7.2.2 --- Graphical Results --- p.90 / Chapter 7.2.3 --- Analysis --- p.90 / Chapter 7.3 --- Problem B --- p.92 / Chapter 7.3.1 --- Data Results --- p.92 / Chapter 7.3.2 --- Graphical Results --- p.94 / Chapter 7.3.3 --- Analysis --- p.96 / Chapter 8 --- Conclusion and Future Work --- p.97 / Chapter 8.1 --- Conclusion --- p.97 / Chapter 8.2 --- Future Work --- p.98 / Chapter A --- Problems Parameters --- p.100 / Chapter A.1 --- Problem A --- p.100 / Chapter A.1.1 --- Parameters of Generating Units --- p.101 / Chapter A.2 --- Problem B --- p.103 / Chapter A.2. --- 1 Parameters of Generating Units --- p.104

by Kin Kwong Leung. / Thesis submitted in: November 1999. / Thesis (M.Phil.)--Chinese University of Hong Kong, 2000. / Includes bibliographical references (leaves 67-[70]). / Abstracts in English and Chinese. / Chapter 1 --- Introduction --- p.1 / Chapter 1.1 --- Code Division Multiple Access (CDMA) --- p.1 / Chapter 1.1.1 --- The Cellular Concept --- p.2 / Chapter 1.2 --- Fading and Power Control --- p.3 / Chapter 1.2.1 --- Large Scale Fading --- p.3 / Chapter 1.2.2 --- Small Scale Fading --- p.4 / Chapter 1.2.3 --- Power Control --- p.5 / Chapter 1.2.4 --- Standard Interference Function --- p.5 / Chapter 1.3 --- Previous Work --- p.6 / Chapter 1.3.1 --- Power Control --- p.6 / Chapter 1.3.2 --- Convergence Analysis --- p.8 / Chapter 1.4 --- Scope of this Thesis --- p.8 / Chapter 1.5 --- Organization of the Thesis --- p.9 / Chapter 2 --- System Model --- p.10 / Chapter 2.1 --- System and Definitions --- p.10 / Chapter 2.2 --- Varying Link Gains Model --- p.11 / Chapter 2.3 --- SIR model in CDMA System --- p.13 / Chapter 2.4 --- Simulation Model --- p.14 / Chapter 3 --- Fade Margin --- p.17 / Chapter 3.1 --- Introduction --- p.17 / Chapter 3.2 --- Fixed-step Power Control Algorithm --- p.18 / Chapter 3.3 --- Definitions and Feasibility of SIR --- p.19 / Chapter 3.3.1 --- Definition --- p.19 / Chapter 3.3.2 --- Feasibility --- p.20 / Chapter 3.4 --- Performance Analysis on Fading Channel --- p.22 / Chapter 3.4.1 --- Single-User --- p.22 / Chapter 3.4.2 --- Multiple-User --- p.24 / Chapter 4 --- Generalized Step Power Control Algorithm --- p.28 / Chapter 4.1 --- Introduction --- p.28 / Chapter 4.2 --- Generalized Fixed Step Power Control Algorithm --- p.29 / Chapter 4.3 --- Existence of the Solution --- p.30 / Chapter 4.4 --- Parameter Optimization --- p.31 / Chapter 4.4.1 --- Single-User --- p.34 / Chapter 4.4.2 --- Multiple-User --- p.37 / Chapter 4.5 --- Performance Analysis --- p.41 / Chapter 4.5.1 --- Single-User --- p.41 / Chapter 4.5.2 --- Multiple-User --- p.42 / Chapter 4.6 --- Hybrid Scheme --- p.47 / Chapter 5 --- Convergence Analysis --- p.49 / Chapter 5.1 --- Introduction --- p.49 / Chapter 5.2 --- Totally Asynchronous Models --- p.50 / Chapter 5.3 --- Normalized Interference Function --- p.52 / Chapter 5.4 --- Existence of Quantized Solution --- p.53 / Chapter 5.5 --- Convergence Theorem --- p.55 / Chapter 6 --- Conclusion and Future Work --- p.64 / Chapter 6.1 --- Conclusion --- p.64 / Chapter 6.2 --- Future Works --- p.65 / Bibliography --- p.67

The voltage stability problem in electric power systems is concerned with the analysis of events and mechanisms that can lead a system into inadmissible operating conditions from the voltage viewpoint. In the worst case, total collapse of the system may result, with disastrous consequences for both electricity utilities and customers. The analysis of this problem has become an important area of research over the past decade due to some instances of voltage collapse that have occurred in electric systems throughout the world. This work addresses the voltage stability problem within the framework of artificial neural networks. Although the field of neural networks was established during the late 1940s, only in the past few years has it experienced rapid development. The neural network approach offers some potential advantages to the solution of problems for which an analytical solution is difficult. Also, efficient and accurate computation may be achieved through neural networks. The first contribution of this work refers to the development of an artificial neural network capable of computing a static voltage stability index, which provides information on the stability of a given operating state in the power system. This analytical tool was implemented as a self-contained computational system which exhibited good accuracy and extremely low processing times when applied to some study cases. Dynamic characteristics of the electrical system in the voltage stability problem are very important. Therefore, in a second stage of the present work, the scope of the research was extended so as to take into account these new aspects. Another neural network-based computational system was developed and implemented with the purpose of providing some information on the behaviour of the electrical system in the immediate future. Examples and case studies are presented throughout the thesis in order to illustrate the most relevant aspects of both artificial neural networks and the computational models developed. A general discussion summarises the main contributions of the present work and topics for further research are outlined.

Digitized by Kansas Correctional Industries / Department: Electrical Engineering.