الفهرس 
INTRODUCTIONOnly 14 pages are availabe for public view
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Abstract
The optimal power flow (OPF) problem deals withhow to find the optimal settings to operate an electric power system. When the operating cost is minimized, the generator schedule is determined by the solution of the OPF problem formulated for the power system in hand. Traditionally, the cost function of each generator is represented by a simple quadratic function. However, the large steam turbine generators usually have a number of steam admission valves that are opened in sequence to obtain over increasing output from the unit. Loading (output) levels at which a new steam admission valve is opened are called valve points. At these levels, discontinuities in the cost curves occur because of the sharp increases in throttle losses. The valve point loading effect is represented by a sinusoid component added to the cost function. This sinusoid component increases the complexity of the OPF problem. In its most general formulation, the OPF problem is a non-linear, non-convex, large- scale, static optimization problem with both continuous and discrete control variables. Even in the absence of non-convex unit operating cost functions, unit prohibited operating zones, and discrete control variables, the OPF problem is non-convex due to the existence of the non- linear alternating current (AC) power flow equality constraints. The presence of discrete control variables, such as switchable shunt devices, transformer tap positions, and phase shifters, further complicates the problem solution. Because the OPF problem is a very large, non-linear mathematical programming problem, it has taken decades to develop efficient algorithms for its solution. Many different mathematical techniques have been employed for its solution. The primary goal of the OPF problem is to minimize the costs of meeting the load demand for a power system while maintaining the security of the system. from the viewpoint of an OPF problem, the br>maintenance of system security requires keeping each device in the power system within its desired operation range at steady state. This will include maximum and minimum outputs for generators’ active and reactive powers, maximum Mega-Volt-Ampere (MVA) flows on transmission lines and transformers, as well as keeping system bus voltages within specified ranges. In this thesis, the optimal power flow (OPF) problem has been solved using a particle swarm optimization (PSO) algorithm, which is a population-based search method. The valve
point loading effects have been considered. Both power systems under normal operating <conditions as well as power systems in a contingency state have been studied. The proposed algorithm has been tested by its application to the 26-bus power system and the IEEE 30-bus power system. The results obtained are promising, where the solutions obtained satisfy the imposed constraints and the cost of generating power agrees with the results obtained by other researchers in the field. The use of capacitors in power systems has many well-known benefits that include improvement of the system power factor, improvement of the system voltage profile, increasing the maximum flow through cables and transformers and reduction of losses due to the compensation of the reactive component of power flow. These benefits depend greatly on.