Showing 4 results for Jalili
M. Abadi, S. Jalili,
Volume 2, Issue 3 (October 2006)
Abstract
Intruders often combine exploits against multiple vulnerabilities in order to
break into the system. Each attack scenario is a sequence of exploits launched by an
intruder that leads to an undesirable state such as access to a database, service disruption,
etc. The collection of possible attack scenarios in a computer network can be represented by
a directed graph, called network attack graph (NAG). The aim of minimization analysis of
network attack graphs is to find a minimum critical set of exploits that completely
disconnect the initial nodes and the goal nodes of the graph. In this paper, we present an ant
colony optimization algorithm, called AntNAG, for minimization analysis of large-scale
network attack graphs. Each ant constructs a critical set of exploits. A local search heuristic
has been used to improve the overall performance of the algorithm. The aim is to find a
minimum critical set of exploits that must be prevented to guarantee no attack scenario is
possible. We compare the performance of the AntNAG with a greedy algorithm for
minimization analysis of several large-scale network attack graphs. The results of the
experiments show that the AntNAG can be successfully used for minimization analysis of
large-scale network attack graphs.
M. Ghaseminezhad, A. Doroudi, S. H. Hosseinian, A. Jalilian,
Volume 17, Issue 1 (March 2021)
Abstract
Nowadays study of input voltage quality on induction motors behavior has become a controversial subject due to the wide application of these motors in the industry. The impact of grid voltage fluctuations on the performance of induction motors can be included in this area. The majority of papers devoted to the influence of voltage fluctuations on the induction motors are focusing only on the solving of d-q state equations or steady-state equivalent circuit analysis. In this paper, a new approach to this issue is investigated by field analysis which studies the effects of voltage fluctuations on the magnetic fluxes of induction motors. New analytical expressions to approximate the airgap flux density and the torque under-voltage fluctuation conditions are presented. These characteristics are also calculated directly by the finite-element method considering the magnetic saturation and the harmonic fields. Finally, experimental results on a typical induction motor are employed to validate the accuracy of analytical and simulation results.
M. Habibolahzadeh, A. Jalilian,
Volume 17, Issue 2 (June 2021)
Abstract
Electric traction trains are huge non-linear single-phase loads influencing adversely on power quality parameters on the grid side. Hybrid power quality conditioner (HPQC) has been utilized to compensate current unbalance, harmonics, and low power factor in the co-phase traction system simultaneously. By incrementing the traction load, the rating of the HPQC increases and may constraints its application. In this paper, a C-type filter is designed to compensate for some part of the load reactive power while the HPQC compensates the remaining part of the load reactive power. Hence, the capacity of the HPQC is reduced in full compensation (FC) mode compared to the conventional configuration. The satisfactory performance of the HPQC is associated with its DC-link operating voltage. Therefore, the Genetic algorithm (G.A) is adopted to optimize the DC-link voltage performance. Simulation verifications are performed to illustrate the usefulness of the proposed configuration. The simulation results show an 18.86% reduction in the rating of the HPQC with optimized DC-link voltage.
A. Karimpour, A. M. Amani, M. Karimpour, M. Jalili,
Volume 17, Issue 4 (December 2021)
Abstract
This paper studies the voltage regulation problem in DC microgrids in the presence of variable loads. DC microgrids generally include several Distributed Generation Units (DGUs), connected to electrical loads through DC power lines. The variable nature of loads at each spot, caused for example by moving electric vehicles, may cause voltage deregulation in the grid. To reduce this undesired effect, this study proposes an incentive-based load management strategy to balance the loads connected to the grid. The electricity price at each node of the grid is considered to be dependent on its voltage. This guide moving customers to connect to cheaper connection points, and ultimately results in even load distribution. Simulations show the improvement in the voltage regulation, power loss, and efficiency of the grid even when only a small portion of customers accept the proposed incentive.
