فهرست مطالب محسن نیاستی

The improved limiting parameter method of Monte Carlo is used in this study to estimate the impact of back-flashover (BF) due to lightning and provide an evaluation criterion for the insulation risk of the transformer in the high-voltage substation. In order to avoid the computational burden of the transient-state simulation, the Monte Carlo (MC) simulation method is combined with the limiting parameter method while taking into account the environmental conditions governing the high-voltage substation. Insulating behavior may be different before or after applying stress. Additionally, it is necessary to consider how the presence of environmental pollutants affects on BF lightning overvoltage amplitude. Therefore, the voltage-time-dependent strength accumulation characteristic has been developed in this study based on the transformer's non-self-healing behavior when exposed to various insulation stresses. By selecting appropriate distribution of expected strokes to estimate insulation risk, the finite area MC method that is being proposed calculates the insulation risk of the transformer based on the transient overvoltage that appears at the transformer terminals. Also discussed is the relationship between BF lightning and the contamination level of the insulation under the stresses brought on by lightning strikes. In this manner, the insulation coordination of the transformer can be known with the least number of calculations by using the structural data of the substation, the lines connected to it, and the transformer. The simulation results presented in this study were performed in a real sample network.The results showed an 18 percent increase in insulation risk considering the effect of environmental condition.

Due to the increasing load growth and expansion and significant changes in structure of electricity distribution networks, the issues related to the optimization of these networks face many challenges. Optimal placement and capacity of Distribution substations and their feeder networks are among the important issues of optimization of distribution networks from technical and economic viewpoints. In this paper, considering two important factors including loss reduction and improvement of reliability in distribution networks, a new multi-objective function was presented for optimal placement of location and capacity of Distribution substations based on their service area. The proposed objective function includes all construction and operation costs of equipment, loss costs, and reliability index (Energy Not Supplied). The Artificial Bee Colony (ABC) algorithm was applied to optimize the proposed objective function with the purpose of determining the optimal placement and capacity of substations of two sample distribution networks. A comparison of results obtained from optimization of the proposed objective function by the Artificial Bee Colony (ABC) algorithm with results of other algorithms in two sample networks indicates the efficiency and effectiveness of the proposed algorithm and objective function.

One of the most critical and complex issues in long-term planning of distribution networks is the optimal placement of distribution transformers. In this paper, the optimal placement of distribution transformers was investigated based on a complete and multi-objective function. In the proposed method, location, optimal capacity, and the service area are determined by minimizing costs (investment, operation, reliability) and improving reliability and power quality parameters (voltage drop) due to electric restrictions (radial structure, voltage drop and equipment capacities). The planning of distribution networks is complicated due to the existence of numerous and multiple-criteria decision-making variables in objective functions; hence in this paper, the symbiotic organisms search (SOS) algorithm was used as a new heuristic optimization algorithm to solve the problem of long-term planning of distribution networks. The proposed method is tested on a real distribution network to evaluate the performance of the proposed algorithm,  Comparing the results of the proposed algorithm with the results of studies with genetic algorithms (GA), biogeography-based optimization (BBO) and imperialist competitive algorithm (ICA), indicates the performance and advantages of the proposed algorithm over other algorithms.

Expand and upgrade distribution networks، connection of DG to distribution networks and parallel network with each other (in order to increase the reliability of the system) are the main factors in increasing short circuit current in distribution networks. Thus، the fault current limiting is essential in developing distribution networks. Using of fault current limiters is one of the methods to reduce the amplitude of the fault current. Performance of this equipment is depends on the fault current limiting parameters and its position. Change in its position could be increased short circuit current. This paper investigates the effect of fault current limiting on a micro grid consists of a wind turbine and fuel cell. Also، suitable positions for the installation of fault current limiters have been studied. The simulation results show the effect of superconducting fault current limiting and the install location in current decreasing the amplitude of error.

Most modern DC electrified railway systems use a totally floating earth as their grounding strategy. A well-known problem related with totally floating systems is that the touch potentials can be dangerously high. In order to reduce the voltages on rails, several devices exist. Most of these devices allow a direct connection to earth when a certain voltage threshold is exceeded. In this paper, the working principles of these devices are given and the effect of certain parameters related with these devices on the minimum achievable touch potentials is investigated.