Stochastic Multiobjective Distribution Systems Phase Balancing Considering Distributed Energy Resources

Abstract

A distribution system is usually unbalanced due to its various loads types with different connection patterns. So phase balancing is taken into consideration in distribution networks. Rephasing is the most effective method for phase balancing of distribution networks but the distributed generation (DG) effect on distribution networks phase balancing is also considerable. In this paper, smart distribution feeder has got balanced by DG sizing and rephasing strategy simultaneously. This combination has a significant influence on network phase balancing in addition to the system cost reduction. The problem is investigated in the deterministic and stochastic frameworks. In the stochastic framework, uncertainty related to hourly wind power and load is modeled using a scenario-based method. After the generated scenarios reduction, fuzzy multiobjective phase balancing (rephasing and DG sizing) based on θ-modified bat algorithm (θ-MBA) is applied to each reduced scenario. Finally, the obtained results of phase balancing in these scenarios are aggregated. The results of stochastic phase balancing are more realistic than deterministic phase balancing.