Flower pollination algorithm for distribution system phase balancing considering variable demand

Abstract

Power Distribution systems are one of the most critical links between utility and utility customer. Control of power loss in distribution systems are very much essential considering the economical aspects. Reconfiguration, Capacitor Placement and Phase Balancing are the different methods practiced for power loss reduction. Due to the unbalanced nature of the distribution system, phase balancing is considered as the effective one amongst the above mentioned three methods. Unbalanced feeders not only increase power losses and the risk of overload situations, but they also affect power quality and electricity price. A severely unbalanced circuit can result in excessive voltage drops on the heavily phase. Even a feeder system is designed as a balanced feeder based on the given load data, load prediction errors and unbalanced load growth will induce feeder imbalance. Phase swapping is a direct and effective way to balance a feeder in terms of phases. It has been practiced by engineers based on their previous experiences, and trial and error for phase balancing. In this paper, a phase swapping algorithm based on hybrid Fuzzy-Flower Pollination Algorithm (FFPA) has been developed to minimize the phase current deviation amongst the phases. Flower Pollination Algorithm is used to optimize the fitness value and fuzzy used to format the fitness function integrating multi-objectives. The validation of the proposed algorithm is done through two standard test cases and simulation results are compared with literature.