The main objective of the Thesis is to work out the methodology aimed to develop a closely integrated electricity network model to be used for real time calculations, and afterwards, based on this methodology, to develop a model of a closely integrated electricity network, which would be applicable in real time calculations of active and reactive power.

This research proposes an efficient reliability modeling and simulation methodology in power systems to include photovoltaic units, wind farms and storage. Energy losses by wake effect in a wind farm are incorporated. Using the wake model, wind shade, shear effect and wind direction are also reflected. For solar modules with titled surface, more accurate hourly photovoltaic power in a specific location is calculated with the physical specifications. There exists a certain level of correlation between renewable energy and load. This work uses clustering algorithms to consider those correlated variables. Different approaches are presented and applied to the composite power system, and compared with different scenarios using reliability analysis and simulation. To verify the results, reliability indices are compared with those from original data. As the penetration of renewables increases, the reliability issues will become more important because of the intermittent and non-dispatchable nature of these sources of power. Storage can provide the ability to regulate these fluctuations. The use of storage is investigated in this research. To determine the operating states and transition times of all turbines, Monte Carlo is used for system simulation in the thesis. A conventional power system from IEEE Reliability Test Systems is used with transmission line capacity, and wind and solar data are from National Climatic Data Center and National Renewal Energy Laboratory. The results show that the proposed technique is effective and efficient in practical applications for reliability analysis.

No description available.

Conventional power system stabilisers (PSS) are designed to eliminate poorly damped, low frequency power oscillations that occur between remote generating pools or power stations, due to different types and settings of the automatic voltage regulators at different power stations. The supplementary control of the PSS is exerted on the power system through a generator's excitation system to which the PSS is attached. In order to design these conventional power system stabilisers , requires accurate system data and an in-depth knowledge of classical control theory. This thesis investigates the use of an intelligent, non-linear PSS that utilises fuzzy logic techniques. Others have proposed the concept of such a PSS, since it does not require accurate system data. This thesis describes the basic aspects of power system stability . Thereafter the methods of modelling synchronous machines in a multi-machine power system are presented. The sample power system being studied and the simulation packages used in the investigations are introduced and the methods involved to design and tune a conventional power system stabiliser using classical control theory and design methods proposed by others, are discussed. The general concept of fuzzy logic is introduced and the application of fuzzy logic techniques to controller design is explained. Using the principles of fuzzy logic controller design, a fuzzy logic power system stabiliser utilising 9 rules is designed and tuned for the multi-machine power system under investigation. The fuzzy logic stabiliser is then applied to a synchronous motor in a pump storage scheme. Previous work has applied fuzzy logic stabilisers only to synchronous generators . To further compare the performance of the 9 rule fuzzy stabiliser, a 49 rule stabiliser developed by other researchers, and adapted to operate on the synchronous motor, is evaluated. Computer simulated results of each of the stabiliser's performances are presented. The results of the 9 rule fuzzy stabiliser are compared with the performance of a conventional linear stabiliser as well as with a 49 rule fuzzy stabiliser. The robustness properties of the fuzzy stabilisers are evaluated. The results further prove that with proper membership function selection, a simple fuzzy stabiliser that demands very little computational overheads can be achieved to provide adequate system damping. / Thesis (M.Sc. Eng.)-University of Natal, Durban, 2003.

This thesis investigates the design of damping controllers to alleviate the problem of low frequency electro-mechanical oscillations in power systems. The operating point and network parameters of power systems are continually changing, resulting in changes in system dynamics. The conventional controller design methodology has therefore come under increasing scrutiny for its lack of considerations for robustness. The thesis first outlines the conventional design of a power system stabilizer (PSS) and then applies two robust techniques (Hoo and Quantitative Feedback Theory, QFT) to the design problem. The single machine infinite bus (SMIB) model is used to illustrate the procedure for all three design techniques. The final design is undertaken to illustrate the more important problem of robust multi-machine PSS design using QFT. The design requires linearised models of the multi-machine system. A brief discussion is given on how these can be obtained. An introduction to decentralized control design in QFT is included to support the multi-machine design. Chapter three proceeds through the design steps required to generate a conventional PSS. The technique is shown to be simple for a given set of operating conditions. The controller is shown to be adequately robust over the given set of operating conditions albeit not by design. Chapter four introduces a design technique that directly addresses robustness issues during the controller design. For a restricted range of operating conditions the designed controller demonstrates the desired robustness and performance characteristics. The inherent difficulties with Hoo in PSS design become more apparent as the operating range is extended. Chapter five introduces the second robust controller design technique. QFT is shown to be more adept at dealing with increased operating ranges and changing specifications in the single-machine infinite-bus case. The controller is easy to generate and performs well over the entire range of operating conditions. QFT is also applied to the controller design for a four-machine study system. The design is a marginally more complex than in the single machine case but is still easily accomplished. This thesis confirms previous attempts at solving the design problem using the methods outlined above. The performance of all controllers is assessed for small and large disturbances using non-linear time domain simulations with models developed using PSCAD/EMTDC and MATLAB. / Thesis (M.Sc.)-University of Natal,Durban, 2002.

The thesis introduces an approach for obtaining higher level decision support information using electromagnetic transient (EMT) simulation programs. In this approach, a suite of higher level driver programs (decision support tools) control the simulator to gain important information about the system being simulated. These tools conduct a sequence of simulation runs, in each of which the study parameters are carefully selected based on the observations of the earlier runs in the sequence. In this research two such tools have been developed in conjunction with the PSCAD/EMTDC electromagnetic transient simulation program. The first tool is an improved optimization algorithm, which is used for automatic optimization of the system parameters to achieve a desired performance. This algorithm improves the capabilities of the previously reported method of optimization-enabled electromagnetic transient simulation by using an enhanced gradient-based optimization algorithm with constraint handling techniques. In addition to allow handling of design problems with more than one objective the thesis proposes to augment the optimization tool with the technique of Pareto optimality. A sequence of optimization runs are conducted to obtain the Pareto frontier, which quantifies the tradeoffs between the design objectives. The frontier can be used by the designer for decision making process. The second tool developed in this research helps the designer to study the effects of uncertainties in a design. By using a similar multiple-run approach this sensitivity analysis tool provides surrogate models of the system, which are simple mathematical functions that represent different aspects of the system performance. These models allow the designer to analyze the effects of uncertainties on system performance without having to conduct any further time-consuming EMT simulations. In this research it has been also proposed to add probabilistic analysis capabilities to the developed sensitivity analysis tool. Since probabilistic analysis of a system using conventional techniques (e.g. Monte-Carlo simulations) normally requires a large number of EMT simulation runs, using surrogate models instead of the actual simulation runs yields significant savings in terms of shortened simulation time. A number of examples have been used throughout the thesis to demonstrate the application and usefulness of the proposed tools.

The fast clearing of faults is essential for preventing equipment damage and preserving the stability of the power transmission systems with smaller operating margins. This thesis examined the application of fault generated transients for fast detection and isolation of faults in a transmission system. The basis of the transient based protection scheme developed and implemented in this thesis is the fault current directions identified by a set of relays located at different nodes of the system. The direction of the fault currents relative to a relay location is determined by comparing the signs of the wavelet coefficients of the currents measured in all branches connected to the node. The faulted segment can be identified by combining the fault directions identified at different locations in the system. In order to facilitate this, each relay is linked with the relays located at the adjacent nodes through a telecommunication network. In order to prevent possible malfunctioning of relays due to transients originating from non-fault related events, a transient recognition system to supervise the relays is proposed. The applicability of different classification methods to develop a reliable transient recognition system was examined. A Hidden Markov Model classifier that utilizes the energies associated with the wavelet coefficients of the measured currents as input features was selected as the most suitable solution. Performance of the protection scheme was evaluated using a high voltage transmission system simulated in PSCAD/EMTDC simulation software. The custom models required to simulate the complete protection scheme were implemented in PSCAD/EMTDC. The effects of various factors such as fault impedance, signal noise, fault inception angle and current transformer saturation were investigated. The performance of the protection scheme was also tested with the field recorded signals. Hardware prototypes of the fault direction identification scheme and the transient classification system were implemented and tested under different practical scenarios using input signals generated with a real-time waveform playback instrument. The test results presented in this thesis successfully demonstrate the potential of using transient signals embedded in currents for detection, localization and recognition of faults in transmission networks in a fast and reliable manner.

The present thesis tackles the problem of on-line steady state security assessment in electric power transmission networks. The contingencies examined include generation shift as well as line (transformer) outages. / The methodology developed is Pattern Recognition-motivated although not entirely within the frame of traditional statistical Pattern Recognition. / Due to the fact that training samples are rather expensive to obtain in electric power engineering, our first concern was to develop and implement algorithms carrying out the task of intelligently acquiring training points. It is found that these algorithms, permit to substantially reduce the amount of off-line computational effort while, at the same time, the coherency and impartiality of the information contained in the training sets is enhanced. / A new scheme for security assessment (equally applicable for real time security screening) was developed based on the concept of the hyperellipsoids of confidence. It is shown that by proper utilization of the hyperellipsoids of confidence, uncertainty in real time decision making (directly related to the misclassification error) is circumvented. The results of the new methodology were verified by full scale ac simulations. / Finally, the usefulness and potential applicability of the new scheme is demonstrated for EHV equivalents. Its merits are simplicity and reliability in real time environment.

This dissertation formulates and develops models and solution approaches for plug-in electric vehicle (PEV) charging station installation. The models are formulated in the form of bilevel programming and stochastic programming problems, while a meta-heuristic method, genetic algorithm, and Monte Carlo bounding techniques are used to solve the problems. Demand for PEVs is increasing with the growing concerns about environment pollution, energy resources, and the economy. However, battery capacity in PEVs is still limited and represents one of the key barriers to a more widespread adoption of PEVs. It is expected that drivers who have long-distance commutes hesitate to replace their internal combustion engine vehicles with PEVs due to range anxiety. To address this concern, PEV infrastructure can be developed to provide re-fully status when they are needed. This dissertation is primarily focused on the development of mathematical models that can be used to support decisions regarding a charging station location and installation problem. The major parts of developing the models included identification of the problem, development of mathematical models in the form of bilevel and stochastic programming problems, and development of a solution approach using a meta-heuristic method. PEV parking building problem was formulated as a bilevel programming problem in order to consider interaction between transportation flow and a manager decisions, while the charging station installation problem was formulated as a stochastic programming problem in order to consider uncertainty in parameters. In order to find the best-quality solution, a genetic algorithm method was used because the formulation problems are NP-hard. In addition, the Monte Carlo bounding method was used to solve the stochastic program with continuous distributions. Managerial implications and recommendations for PEV parking building developers and managers were suggested in terms of sensitivity analysis. First, in the planning stage, the developer of the PEV parking building should consider long-term changes in future traffic flow and locate a PEV parking building closer to the node with the highest destination trip rate. Second, to attract more parking users, the operator needs to consider the walkability of walking links.

The Estimation of Thevenin Equivalent Parameters is useful for System Monitoring and Protection. We studied a method for estimating the Thevenin equivalent circuits. We then studied two applications including voltage stability and fault location. A study of the concepts of Voltage Stability is done in the initial part of this thesis. A Six Bus Power System Model was simulated using MATLAB SIMULINK®. Subsequently, the Thevenin Parameters were calculated. The results were then used for two purposes, to calculate the Maximum Power that can be delivered and for Fault Location.