الفهرس يوجد فقط 14 صفحة متاحة للعرض العام
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المستخلص
The increasing demand for an optimal power flow (OPF) tool for studying power systems has been on the increase since the first OPF paper was presented in the 60’s . There are various existing models for the OPF problem. Some models include only the real power subproblem or only the reactive power subproblem. Such a decoupled model suffices in some cases but can lead to suboptimal solutions or may even be infeasible. Another common difference between OPF models is in the objective function. The objectives can be one of : minimize transmission losses, minimize deviations from a specified operating point, minimize the number of control variables that are altered, or, minimize the operating cost . The models also differ in how they handle inequality constraints. Modeling the inequality constraints using hard limits can lead to uneconomical solutions. Minimizing the operating cost is the most commonly employed objective.
This thesis proposed a method to solve this problem in two seperatly stages, the first to find the optimal values for the fuel cost and the results are used as initial values to the second stage to find the optimal fuel emissions then repeat these steps untile reach the optimal results. Also there is another proposed method where the cost function and the emission function are combined to form the multi-objective function using the price penalty factors. The artificial networks are used to solve this problem and reach the optimal values of the fuel cost and fuel emissions.