An improved artificial bee colony optimization algorithm based on orthogonal learning for optimal power flow problem

2017 ◽  
Vol 61 ◽  
pp. 163-172 ◽  
Author(s):  
Wenlei Bai ◽  
Ibrahim Eke ◽  
Kwang Y. Lee
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Artificial Bee Colony ◽  
Flow Problem ◽  
Artificial Bee Colony Optimization ◽  
Bee Colony ◽  
Optimal Power ◽  
Bee Colony Optimization ◽  
Orthogonal Learning ◽  
Power Flow Problem

scholarly journals Artificial Bee Colony Algorithm for Solving Optimal Power Flow Problem

2013 ◽  
Vol 2013 ◽  
pp. 1-9 ◽  
Author(s):  
Luong Le Dinh ◽  
Dieu Vo Ngoc ◽  
Pandian Vasant
Keyword(s):  
Power Flow ◽  
Optimal Power Flow ◽  
Artificial Bee Colony ◽  
Optimization Method ◽  
Capacity Limits ◽  
Abc Algorithm ◽  
Bee Colony ◽  
Optimal Power ◽  
Line Flow ◽  
Power Flow Problem

This paper proposes an artificial bee colony (ABC) algorithm for solving optimal power flow (OPF) problem. The objective of the OPF problem is to minimize total cost of thermal units while satisfying the unit and system constraints such as generator capacity limits, power balance, line flow limits, bus voltages limits, and transformer tap settings limits. The ABC algorithm is an optimization method inspired from the foraging behavior of honey bees. The proposed algorithm has been tested on the IEEE 30-bus, 57-bus, and 118-bus systems. The numerical results have indicated that the proposed algorithm can find high quality solution for the problem in a fast manner via the result comparisons with other methods in the literature. Therefore, the proposed ABC algorithm can be a favorable method for solving the OPF problem.

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