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

Author(s):Pan Chaoa, Lv Jiahuia, Meng Taob
aSchool of Electrical Engineering, Northeast Dianli University, Jilin 132012, China
bElectrical Power Research Institute, State Grid Jilin Electric Power Co.Ltd, Changchun 130001, China
International Journal of Smart Grid and Clean Energy, vol. 5, no. 4, October 2016: pp. 237-244
ISSN: 2315-4462 (Print)
ISSN: 2373-3594 (Online)
Digital Object Identifier: 10.12720/sgce.5.4.237-244

Abstract: 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.

Keywords: Fruit fly optimization algorithm, power distribution network, distributed generation, multi-objective optimization, comprehensive membership degree

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