Showing 3 results for Aliakbar-Golkar
A. Hajizadeh, M. Aliakbar-Golkar,
Volume 3, Issue 1 (April 2007)
Abstract
The operation of Fuel Cell Distributed Generation (FCDG) systems in
distribution systems is introduced by modeling, controller design, and simulation study of a
Solid Oxide Fuel Cell (SOFC) distributed generation (DG) system. The physical model of
the fuel cell stack and dynamic models of power conditioning units are described. Then,
suitable control architecture based on fuzzy logic control for the overall system is presented
in order to active power control and power quality improvement. A MATLAB/Simulink
simulation model is developed for the SOFC DG system by combining the individual
component models and the controllers designed for the power conditioning units.
Simulation results are given to show the overall system performance including active power
control and voltage regulation capability of the distribution system.
M. Aliakbar-Golkar, Y. Raisee-Gahrooyi,
Volume 4, Issue 4 (October 2008)
Abstract
This paper compares fault position and Monte Carlo methods as the most
common methods in stochastic assessment of voltage sags. To compare their abilities,
symmetrical and unsymmetrical faults with different probability distribution of fault
positions along the lines are applied in a test system. The voltage sag magnitude in different
nodes of test system is calculated. The problem with these two methods is that they require
unknown number of iteration in Monte Carlo Method and number of fault position to
converge to an acceptable solution. This paper proposes a method based on characteristic
behavior of Monte Carlo simulations for determination required number of iteration in
Monte Carlo method.
Mahdi Sedghi, Masoud Aliakbar-Golkar,
Volume 5, Issue 2 (June 2009)
Abstract
Optimal expansion of medium-voltage power networks is a common issue in electrical distribution planning. Minimizing total cost of the objective function with technical constraints and reliability limits, make it a combinatorial problem which should be solved by optimization algorithms. This paper presents a new hybrid simulated annealing and tabu search algorithm for distribution network expansion problem. Proposed hybrid algorithm is based on tabu search and an auxiliary simulated annealing algorithm controls the tabu list of the main algorithm. Also, another auxiliary simulated annealing based algorithm has been added to local searches of the main algorithm to make it more efficient. The numerical results show that the method is very accurate and fast comparing with the other algorithms.
