Comparison between Genetic Algorithms and Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
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A normalized weighting method combined with particle swarm optimization for the connections between distribution transformers and a primary feeder is presented. A multi-objective instead of single formulation for this problem is applied. Six important objectives include power balance, feeder loss, voltage deviation, LCO current, zero and negative unbalance factor are all considered here. The proposed approach can provide a set of flexible solutions using particle swarm optimization by following the intention of decision makers. Comparative studies on actual Tai-power systems are given to demonstrate the effectiveness of the phase load balancing and the improvement of operation efficiency for the proposed method.