Optimal configuration of distributed generation based on improved fruit fly optimization algorithm

Optimal configuration of distributed generation in power distribution network is researched in this paper. Considering investment benefit, voltage quality and power loss of system, and a multi-objective optimal configuration model is established with fuzzy technique, which could efficiently solve the excessive optimization problem for different dimension of targets. A new bionic intelligence algorithm-fruit fly optimization algorithm is improved and the operation of attraction and repulsion is introduced into this algorithm by learning the chemotaxis of bacteria in foraging process to improve the population diversity and reduce the probability of falling into local optimization. Simulation results of IEEE33 node system demonstrated that, compared with the traditional fruit fly optimization algorithm and particle swarm optimization algorithm, improved fruit fly optimization algorithm has great advantage in optimization speed and solution accuracy, and is able to search the optimal configuration rapidly and effectively, which verify the validity and reasonability of this improved algorithm.