A hybrid self-adaptive particle swarm optimization and modified shuffled frog leaping algorithm for distribution feeder reconfiguration

作者：Niknam Taher^*; Farsani Ehsan Azad

来源：Engineering Applications of Artificial Intelligence, 2010, 23(8): 1340-1349.

DOI：10.1016/j.engappai.2010.02.005

• Evolutionary algorithms (EA)
• Self adaptive particle swarm optimization (SAPSO)
• Discrete particle swarm optimization (DPSO)
• Binary particle swarm optimization (BPSO)
• Modified shuffled frog leaping algorithm (MSFLA)
• Distribution feeder reconfiguration (DFR)

One of the very important way to save the electrical energy in distribution system is network reconfiguration for loss reduction This paper proposes a new hybrid evolutionary algorithm for solving the distribution feeder reconfiguration (DFR) problem The proposed hybrid evolutionary algorithm is the combination of SAPSO (self-adaptive particle swarm optimization) and MSFLA (modified shuffled frog leaping algorithm) called SAPSO-MSFLA which can find optimal configuration of distribution network In the PSO algorithm appropriate adjustment of the parameters is cumbersome and usually requires a lot of time and effort Therefore a self-adaptive framework is proposed to improve the robustness of the PSO also in the modified shuffled frog leaping algorithm (MSFLA) to Improve the performance of algorithm a new frog leaping rule is proposed to improve the local exploration of the SFLA The main idea of integrating SAPSO and MSFLA is to use their advantages and avoid their disadvantages The proposed algorithm is tested on two distr