Abstract
This paper presents a new algorithm for multiobjective distribution feeder reconfiguration (DFR) problem, while uncertainties of the load and wind generators are considered in the stochastic framework. In order to take the uncertainties into account, a probabilistic distribution load flow technique is adopted using point estimate method. The proposed multiobjective framework can optimize different objective functions including total power losses and voltage deviations simultaneously. As the result of conflicting behavior of these objective functions, a max-min decision maker is used to model operators’ preferences for trading off between these objectives. In addition, a novel and powerful optimization algorithm based on improved honey bee mating optimization is proposed to handle the multiobjective DFR problem sufficiently. Finally, the proposed framework is applied on two test systems in order to prove its efficiency and feasibility in comparison with the other methods in the area.
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