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Development of a photovoltaic reverse osmosis demineralization fogging for improved gas turbine generation outputLameen, Tariq M. H. January 2018 (has links)
Thesis (Master of Engineering in Electrical Engineering)--Cape Peninsula University of Technology, 2018. / Gas turbines have achieved widespread popularity in industrial fields. This is due to the high power, reliability, high efficiency, and its use of cheap gas as fuel. However, a major draw-back of gas turbines is due to the strong function of ambient air temperature with its output power. With every degree rise in temperature, the power output drops between 0.54 and 0.9 percent. This loss in power poses a significant problem for utilities, power suppliers, and co-generations, especially during the hot seasons when electric power demand and ambient temperatures are high. One way to overcome this drop in output power is to cool the inlet air temperature. There are many different commercially available means to provide turbine inlet cooling. This disserta-tion reviews the various technologies of inlet air cooling with a comprehensive overview of the state-of-the-art of inlet fogging systems. In this technique, water vapour is being used for the cooling purposes. Therefore, the water quality requirements have been considered in this thesis. The fog water is generally demin-eralized through a process of Reverse Osmosis (RO). The drawback of fogging is that it re-quires large amounts of demineralized water. The challenge confronting operators using the fogging system in remote locations is the water scarcity or poor water quality availability. However, in isolated hot areas with high levels of radiation making use of solar PV energy to supply inlet cooling system power requirements is a sustainable approach. The proposed work herein is on the development of a photovoltaic (PV) application for driv-ing the fogging system. The design considered for improved generation of Acaica power plant in Cape Town, South Africa. In addition, this work intends to provide technical infor-mation and requirements of the fogging system design to achieve additional power output gains for the selected power plant.
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Modelling short term probabilistic electricity demand in South AfricaMokhele, Molete January 2016 (has links)
Dissertation submitted for Masters of Science degree in Mathematical Statistics
in the
Faculty of Science,
School of Statistics and Actuarial Science,
University of the Witwatersrand
Johannesburg
May 2016 / Electricity demand in South Africa exhibit some randomness and has some important
implications on scheduling of generating capacity and maintenance plans. This work
focuses on the development of a short term probabilistic forecasting model for the 19:00
hours daily demand. The model incorporates deterministic influences such as; temperature
effects, maximum electricity demand, dummy variables which include the holiday
effects, weekly and monthly seasonal effects. A benchmark model is developed and an
out-of-sample comparison between the two models is undertaken. The study further assesses
the residual demand analysis for risk uncertainty. This information is important
to system operators and utility companies to determine the number of critical peak days
as well as scheduling load flow analysis and dispatching of electricity in South Africa.
Keywords: Semi-parametric additive model, generalized Pareto distribution, extreme
value mixture modelling, non stationary time series, electricity demand
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Decentralized automatic generation control based on optimal linear regulator theoryFu, Sheau-Wei January 2011 (has links)
Digitized by Kansas Correctional Industries
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A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.
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Design of wide-area damping control systems for power system low-frequency inter-area oscillationsZhang, Yang, January 2007 (has links) (PDF)
Thesis (Ph. D. in electrical engineering)--Washington State University, December 2007. / Includes bibliographical references (p. 135-146).
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A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.
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A new evolutionary optimisation method for the operation of power systems with multiple storage resourcesThai, Cau Doan Hoang, Electrical Engineering & Telecommunications, Faculty of Engineering, UNSW January 2000 (has links)
Advanced technologies, a world-wide trend to deregulation of power systems and environmental constraints have attracted increasing interest in the operation of electric power systems with multiple storage resources. Under the competitive pressure of the deregulation, new efficient solution techniques to adapt quickly to the changing marketplace are in demand. This thesis presents a new evolutionary method, Constructive Evolutionary Programming (CEP), for minimising the system operational cost of scheduling electric power systems with multiple storage resources. The method combines the advantages of Constructive Dynamic Programming and Evolutionary Programming. Instead of evolving the "primal" variables such as storage content releases and thermal generator outputs, CEP evolves the piecewise linear convex cost-to-go functions (i.e. the storage content value curves). The multi-stage problem of multi-storage power system scheduling is thus decomposed into many smaller one-stage subproblems with evolved cost-to-go functions. For each evolutionary individual, linear programming is used in the forward pass process to solve the dispatch subproblems and the total system operational cost over the scheduling period is assigned to its fitness. Case studies demonstrate that the proposed method is robust and efficient for multi-storage power systems, particularly large complex hydrothermal system with cascaded and pumped storages. Although the proposed method is in the early stage of development, relying on assumptions of piecewise linear convexity in a deterministic environment, methods for the incorporation of stochastic models, electrical network and nonlinear, non-convex and non-smooth models are discussed. In addition, a number of possible improvements are also outlined. Due to its simplicity but robustness and efficiency, there are potential research directions for the further development of this evolutionary optimisation method.
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Implementation of a SM drive in a voltage-source converter control system with a PCSad/EMTDC simulation software interfaceJohansson, Frank January 2002 (has links)
No description available.
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Evaluation of dynamically controlled resistive braking for the Pacific Northwest power systemRaschio, Peter J. 19 July 1994 (has links)
Today's power systems are undergoing dynamic changes in their operation.
The high cost of capital improvements that include new generation and transmission
projects has prompted power system planners to look for other alternatives in dealing
with increased loads and overall system growth. A dynamic braking resistor is a
device that allows for an increased rating of a transmission system's transient stability
limit. This allows increased power flows over existing transmission lines without the
need to build additional transmission facilities.
This thesis investigates the application of dynamically controlled resistive
braking in the Pacific Northwest power system. Specifically, possible control
alternatives, to replace the present dynamic brake control system at Chief Joseph
station, are examined. This examination includes determination of appropriate
locations for control system input, development of control algorithms, development of
computer and laboratory power system models, and testing and recommendations
based upon the developed control algorithms. / Graduation date: 1995
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Nonlinear control applied to power systemsVedam, Rajkumar 05 August 1994 (has links)
When large disturbances occur in interconnected power systems, there exists the danger
that the power system states may leave an associated region of stability, if timely corrective action
is not taken. Open-loop remedial control actions such as field-forcing, line-tripping, switching of
series-capacitors, energizing braking resistors, etc., are helpful in reducing the effects of the
disturbance, but do not guarantee that the post-fault power system will be stabilized. Linear
controllers are widely used in the power industry, and provide excellent damping when the power
system state is close to the equilibrium. In general, they provide conservative regions of stability.
This study focuses on the development of nonlinear controllers to enhance the stability of
interconnected power systems following large disturbances, and allow stable operation at high
power levels.
There is currently interest in the power industry in using thyristor-controlled series-capacitors
for the dual purpose of exercising tighter control on steady-state power flows and
enhancing system stability. This device is used to implement the nonlinear controller in this
dissertation. A mathematical model of the power system controlled by the thyristor-controlled
series-capacitor is developed for the purpose of controller design.
Discrete-time, nonlinear predictive controllers are derived by minimizing criterion
functions that are quadratic in the output variables over a finite-horizon of interest, with respect to
the control variables. The control policies developed in this manner are centralized in nature. The
stabilizing effect of such controllers is discussed. A potential drawback is the need to have large
prediction horizons to assure stability. In this context, a coordinated-control policy is proposed, in
which the nonlinear predictive controller is designed with a small prediction horizon. For a class of
disturbances, such nonlinear predictive controllers return the power system state to a small
neighborhood of the post-fault equilibrium, where linear controllers provide asymptotic
stabilization and rapid damping. Methods of coordinating the controllers are discussed. Simulation
results are provided on a sample four-machine power system model.
There exists considerable uncertainty in power system models due to constantly shifting
loads and generations, line-switching following disturbances, etc. The performance of fixed-parameter
controllers may not be good when the plant description changes considerably from the
reference. In this context, a bilinear model-based self-tuning controller is proposed for the
stabilization of power systems for a class of faults. A class of generic predictive controllers are
presented for use with the self-tuning controller. Simulation results on single-machine and
multimachine power systems are provided. / Graduation date: 1995
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