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- 저자 : Vahedi Mojtaba (검색결과 4 건)
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Hematian Masoud,Vahedi Mojtaba,Samiei Moghaddam Mahmoud,Salehi Nasrin,Azarfar Azita 대한전기학회 2023 Journal of Electrical Engineering & Technology Vol.18 No.5
The reconfiguration of the smart distribution grid is one of the low-cost and effective ways to improve loss reduction and voltage balance, which has faced important challenges with the presence of issues such as energy storage systems, electric vehicles, demand side management, and fossil distributed generation resources. In recent studies, in addition to considering the reduction of distribution system losses as one of the goals of the optimization problem, reducing the purchase of power from the transmission network in distribution substations has also been considered by researchers. In this paper, a second-order cone optimization model to solve the stochastic dynamic reconfiguration based on a scenario considering renewable energy resources, energy storage systems, electric vehicles, and demand-side management program with fossil distributed generation such as gas-fired and diesel generators resources to improve a multi-objective function including reducing power losses, reducing power purchases at distribution substations and reducing the cost of cutting off renewable energy resources has been proposed. The proposed model is implemented using the Gurobi solver and the Julia programming language, and the results of the IEEE 33-bus network analysis for the day ahead and the 24 h load curve demonstrate the performance of the proposed model.
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Self-Tuning Fuzzy Task Space Controller for Puma 560 Robot
Azita Azarfar,Babak Azarfar,Mojtaba Vahedi 대한전기학회 2021 Journal of Electrical Engineering & Technology Vol.16 No.1
Since in most robot applications the desired paths are determined in task space or Cartesian space, it is important to control the robot arm in task space. In this paper, a fuzzy controller with modifi able scaling factors is proposed to control the robot end-eff ector in task space. The controller is a fuzzy system with a mechanism to change the scaling factors when the error is bounded under a predetermined value. The controller is designed in joint space and is developed to work space by using inverse Jacobian strategy. The simulations results on Puma 560 robot manipulator illustrate the high performance of the presented control method
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The impact of disease characteristics on multiple sclerosis patients’ quality of life
Aziz Rezapour,Abdollah Almasian Kia,Sahar Goodarzi,Mojtaba Hasoumi,Soraya Nouraei Motlagh,Sajad Vahedi 한국역학회 2017 Epidemiology and Health Vol.39 No.-
OBJECTIVES: The aim of this study was to assess the quality of life (QoL) of patients with multiple sclerosis (MS), and to investigate the effects of characteristics of MS such as disease course, severity, and relapses on patients’ QoL. METHODS: This was a cross-sectional study, in which 171 patients were enrolled. Health-related QoL was assessed using the Persian version of the Multiple Sclerosis Quality of Life-54 questionnaire. To measure patients’ disability status, we used the Expanded Disability Status Scale. Other variables included in the study were disease course and relapses of the disease. RESULTS: The average scores for patients’ physical and mental QoL were 60.9±22.3 and 59.5±21.4, respectively. In a bivariate analysis, disease course, severity of the disease, and relapses were significantly associated with the physical and mental health composite scores. In a hierarchal regression analysis, disease course, severity of the disease, and relapses were responsible for 38 and 16% of the variance in physical and mental QoL, respectively. It was also observed that relapses were a strong predictor of both physical and mental QoL. CONCLUSIONS: Our results showed that disease characteristics significantly affected both dimensions of QoL. It is therefore suggest
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Tamizkar Roozbeh,Samiei Moghaddam Mahmoud,Azarfar Azita,Hoseini Abardeh Mohamad,Vahedi Mojtaba 대한전기학회 2024 Journal of Electrical Engineering & Technology Vol.19 No.2
In this paper, an optimization model for transmission and distribution network integration is proposed. The proposed model is a bi-level optimization model formulated as an upper and lower-level problem. The problem of unit commitment in the transmission network as the upper level problem with the aim of reducing operating costs and load shedding as a mixed integer linear programming model and the problem of optimal operation in the distribution network by considering renewable and non-renewable resources along with electric vehicle charging stations (EVCS), it has been considered as a linear model with the aim of reducing the cost of purchasing power from the transmission network and increasing the use of renewable energy and charging power of EVCS. According to the literature, the study gap can be seen in three key points; frstly, it is of great importance to provide a convex model that can guarantee global optimal solutions. The next point is related to the problem-solving time, according to the dimensions and number of variables and parameters in the problem of optimal coordination of the transmission and distribution network, providing a method to achieve global optimal solutions in the shortest time and the last point is related to the modeling of any number of distribution networks is integrated with the transmission network. To solve the proposed bi-level optimization problem, the method of rewriting the optimization problems using Karush–Kuhn–Tucker condition equations, which can model global optimal solutions as well as fast solution time and modeling a large number of distribution networks in the transmission network has been proposed. Several diferent networks have been considered for the validation of the proposed model and method, which proves the results obtained from the simulation of the efciency of the proposed model and method in considering the coordinated operation of transmission and smart distribution networks. The results showed that the proposed method is about 40% faster than the decomposition method and 20% faster than the evolutionary method, and the results obtained are about 7% more optimal than the evolutionary method.
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