الفهرس 
Structure of Deregulated Power SystemsOnly 14 pages are availabe for public view
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Abstract
In this research, it is concerned with solving the Optimal Reactive Power Dispatch (ORPD) algorithm in order to find the steady state operation point which optimizes one or more objective functions such as minimizes real power loss, reactive generation cost, or maximizes reactive power reserves, etc. while maintaining an acceptable system performance in terms of limits on generators’ reactive powers, line flow limits, outputs of various compensating devices. Traditionally, classical optimization methods were used to effectively solve ORPD. But more recently due to deregulation of a power sector, and the development of artificial intelligence techniques, the traditional concepts and practices of power systems are superimposed by an economic market management. So ORPD have become complex.
The use of fuzzy logic leads to revolution in the optimization processes of the power system operation problems such as security and economic problems. Modeling of power system objectives and constraints using different membership functions are considered. The fuzzy modeling improves the ORPD solutions as finding the optimal control settings within its operational range, best tuning of power system variables, and treating the objective functions as another constraints and so very suitable procedure for multiple objective functions. Two shapes of membership degrees namely, triangle and trapezoidal are considered to determine the best control settings.
In this research, one of the artificial intelligence techniques (fuzzy logic techniques) is applied to solve the ORPD optimization problems in both regulated and competitive electricity environments. Also, the effect of preparing preventive control actions on the existing emergency conditions is studied. The proposed procedure for emergency control of reactive power leads to minimize the real power losses as well as prepare the required control actions after the occurrence of different emergency conditions.