Optimal reactive power dispatch using ant colony optimization algorithm

Sensitivity and functionally oriented models for power system planning, operation, and control

“…; J. As it was indicated above, the construction of sensitivities in [2][3][4][5][6][7][8][9][10][11][12][13][14] is based on the use of system Jacobian matrices and encounters limitations. At the same time, the application of experimental design [16][17][18] provides a means for building adequate sensitivity models.…”

“…As an example, it is possible to indicate the problem of voltage and reactive power control in power systems. The techniques for its solution related to applying optimization as well as knowledge based approaches (for instance, [2][3][4][5][6][7][8][9][10][11][12][13][14]) utilize diverse algorithmic modifications of the method [15] allowing the use of the system Jacobian matrices to build sensitivities (by the way, the solution of other power engineering problems with the use of sensitivity models is also based on applying techniques associated with utilizing Jacobian matrices [2]). However, deficient linearization accuracy permits one to use these techniques when perturbations are small (for example, discussion to [3]).…”

Speed control of SRM supplied by photovoltaic system via ant colony optimization algorithm

“…ACO is a multiagent system in which the behavior of each single agent, called artificial ant, is inspired by the behavior of real ants [27]. ACO has been successfully employed to optimization problems in power system such as power quality enhancement [28] and optimal reactive power dispatch [29]. The feature of this technique is different from other methods since it can be implemented easily and flexible for many problems.…”

“…Fuzzy logic control (FLC) [5][6][7][8][9][10], artificial neural network (ANN) [11,12], robust controller [13][14][15] and adaptive controller [16] have been employed to solve the problem of speed control of SRM. Moreover, optimization techniques like genetic algorithm (GA) [17], particle swarm optimization (PSO) [18][19][20][21][22][23][24][25][26][27][28][29], bacteria foraging [21,22], artificial bee colony [23], firefly [24], imperialist competitive algorithm [25] and BAT algorithm [26] have attracted the attention in designing controller and speed control of various motors.…”

ACO based speed control of SRM fed by photovoltaic system

“…ACO is multi-agent system in which the behavior of each single agent, called artificial ant is inspired by the behavior of real ants [25]. ACO has been successfully employed to optimization problems in power system such as power quality enhancement [26], optimal reactive power dispatch [27]. The feature of this technique is different from other method since it can be implemented easily and flexible for many problems.…”