Gradient-based artificial bee colony for damping controllers design

Abstract

A novel optimization algorithm by combining the artificial bee colony (ABC) algorithm and the sequential quadratic programming (SQP), that is the gradient based ABC algorithm, is presented to resolve the problems of global optimization and inter-area oscillations damping in power system. The proposed algorithm merges the global exploration ability of the artificial bee colony to converge quickly to a near optimum resolution, and the correct local exploitation capacity of the sequential quadratic programming to accelerate the search process and discover a correct solution. To show the feasibility and efficiency of the new method, numerical result is investigated on the New England system by tuning a power system stabilizer and a controller for the static VAR compensator. The proposed gradient based ABC algorithm is compared with ABC. The simulations studies demonstrate that the proposed algorithm based designed damping controllers perform better than controller designed by ABC.

A Novel Optimization Algorithm Combing Gbest-Guided Artificial Bee Colony Algorithm with Variable Gradients

“…In addition to gdbABC [31], ABC-SQP [15] and GdABC [16] also apply gradient information to Newton's method. As a result of searching along the gradient direction, they bring the results of new candidate solutions closer to the optimal value.…”

“…In recent years, some novel algorithms based on gradient information have been brought forward to modify the ABC algorithm. For example, a hybrid algorithm called ABC-SQP was developed by Eslami [15]. It combines the artificial bee colony algorithm with sequential quadratic programming.…”