Optimal Placement of GEV Aggregation in Smart Grid: An Evolutionary Computation Algorithm Approach

摘要

Self-adaptive firefly algorithm (SAFA) is proposed for optimal placement of gridable electric vehicle (GEV) aggregation in smart grid in this paper. An objective function is developed to minimize power losses and maximize voltage profile. The load flow study is carried out on IEEE 33 bus test system and it is noted that timely placement of GEV aggregation in the power network will lead to reduction in the active/reactive power losses and improvement in voltage. The results are compared with other methods, and the proposed algorithm yields promising results.