This paper presents a new method to maximize load restoration in faulted condition in power systems. Control variables which are used to restore maximum load include tap of power transformers, generation rescheduling, and load shedding in the worst case. Modeling is don More
This paper presents a new method to maximize load restoration in faulted condition in power systems. Control variables which are used to restore maximum load include tap of power transformers, generation rescheduling, and load shedding in the worst case. Modeling is done in three stages with various control variables arrangements. In the first stage of modeling, power transformer tap is used as a control variable. In the second stage, power transformers taps and generations rescheduling are considered. In the last stage, load shedding as another variable is added to decision variable spaces. Since the number of variables is high and final solution space can be nonlinear, genetic algorithm is used in the optimization process. The capabilities of the proposed method were assessed using IEEE-RTS test system with satisfactory results.
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