Showing 6 results for Salehi
A. Salehi Dobakhshari, M. Fotuhi-Firuzabad,
Volume 5, Issue 1 (Vol.5 No.1 2008)
Abstract
The increase in fossil fuel prices has resulted in growing utilization of renewable energy sources in power systems. Wind energy as an economical source of energy has experienced the fastest growth among other energy sources. Traditionally, renewable energy sources as a result of their random nature have not been considered in the process of generation expansion planning. The increase in fossil fuel prices and their scarcity in the near future necessitate incorporating wind power in generation expansion planning. This paper studies the utilization of wind power in generation planning considering reliability constraints. Simulation results show that even though wind energy may make a major contribution to generation capacity planning, reliability limitations hinder full utilization of potential wind power. Therefore, conventional generating units should still be taken into account in generation planning while satisfying system reliability criteria.
Mr. Mohammad Javad Kiani, Dr. Alireza Salehi,
Volume 13, Issue 4 (Vol.13 No.4 2017)
Abstract
In this paper, the designing and nano-manufacturing of the SnO2 sensors by the Dip-Coating method is reported to detect CO2 in a gaseous environment by its characteristic absorption. In addition, in order to prepare the Sol-Gel solution, SnCl2 as a primary material with different concentration is selected to deposit in diverse thicknesses. After the SnO2 deposited thin-film with different thicknesses, the electrical characteristic of sensors is obtained with varied both thicknesses and concentration of Co gas. Finally, various measuring of producing gas sensor show suitable sensitivity and quality for Dip-Coating method.
Dr. R. Dashti, Mr. S. M. Salehizadeh,
Volume 14, Issue 1 (IAEEE_No.1_Vol.14 2017)
Abstract
Power distribution feeders contains many laterals, sub-laterals, different number of circuit line, load taps, balanced and unbalanced load, different type of lines (cable or overhead), different cross-sections and numerous distribution transformers with different capacities. Moreover, the voltage and current are measured only at the beginning of the feeder. Thus, fault location is very complex. Because of lack of public electrical MV line corridors and load increasing cause to increase the double circuit lines. Consequently, locating faults in a double circuit line need to special fault-location algorithms. In this article a new method for fault location in double circuited MV power distribution lines is proposed. In this method the impedance based method is improved for locating fault in double circuit distribution networks using the precise line model. This method is tested in a 13 bus IEEE network in different conditions such as various fault resistances and different fault start angles in various distances. The results from the Matlab’s simulation show high accuracy and validity of the proposed method.
S. M. Salehian, H. Hasanvand, B. Mozafari,
Volume 14, Issue 4 (JIAEEE Vol.14 No.4 2018)
Abstract
In this paper, damping of interarea oscillations using simultaneous coordination of static Var compensator (SVC) and power system stabilizer (PSS) is considered. To be effective in damping of oscillations, the best-input signal of power oscillation damper (POD) associated with SVC is selected using Hankel singular values (HSVs), and right-hand plane zeros (RHP-zeros). The 4-machine-2 area standard test system, under different system configurations and loading conditions, is employed to illustrate the performance and robustness of the proposed controller. Eigenvalue analysis and nonlinear time domain simulation results demonstrate the effectiveness of the proposed technique to mitigate interarea oscillations under various operating conditions.
Sobhan Dorahaki, Dr Amir Abdollahi, Dr Zeinolabedin Sadeghi, Dr. Masoud Rashidinejad, Dr Mohammad Reza Salehizadeh,
Volume 19, Issue 1 (JIAEEE Vol.19 No.1 2022)
Abstract
Energy and water are two important factors that are crucial for human survival. In an energy hub, integrated management of water and multi-type of energies such as electrical power, gas, and thermal power increases the economic efficiency of using vital resources. One of the major challenges that deter the effectiveness of this integrated management is the electricity price uncertainties of the upstream market. To address this problem, this paper provides a novel mathematical model along with a robust optimization approach for uncertainty management in smart water and energy hubs. In the proposed robust uncertainty approach, the objective function is optimized subject to the uncertainty set of the problem. Therefore, the optimal solution of the proposed optimization problem is an effective point referring to the amount of specified uncertainty budget by the energy hub system operator. Moreover, a new water infrastructure including a water desalination system and water storage is considered in the proposed smart water and energy hubs. The proposed power and water robust optimization (PWRO) is a Mixed Integer Linear Programing (MILP) model and is solved by CPLEX solver in GAMS environment. The effectiveness of the proposed approach is examined in a case study. Results show that the operation cost of the proposed model increases 1.6 % percent approximately in the worst case. However, the robustness of the system is significantly increased.
Mostafa Ersali Salehi Nasab, Sakineh Seydi,
Volume 22, Issue 2 (JIAEEE Vol.22 No.2 2025)
Abstract
Artificial neural networks are a subset of machine learning inspired by the biological neural networks of the human brain and have the capability to learn. These networks are applied in various fields, including natural language processing, pattern recognition, image processing, computer vision, and many other areas. CNNs (Convolutional Neural Networks) are an example of these networks that have a layered structure, with convolution being their main operation. Due to the high volume of computations and the flow of data in these networks, there is an increased need for bandwidth and memory transfers. Recent researches have shown that the energy consumption and access time of external memory are 200x and 10x greater than internal memory respectively, which leads to increased energy consumption and an imbalance in the data path topology.
One of the main solutions to reduce energy consumption is to increase data reuse and reduce the number of accesses to external memory. Maximizing data usage reduces the number of data movements and memory accesses. One method for data reuse is loop-level scheduling and applying tiling techniques. This paper models the relationship between the number of accesses to external memory when using tiling. This model is presented as a mathematical formula that can determine the exact number of DRAM accesses based on network parameters and the tile size. Then, in an optimization problem, optimal parameters are obtained with the goal of minimizing the use of external memory and establishing the relationship between network configuration parameters and tile size.
