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Showing 3 results for Jafari
Design of High-Efficiency and Low-Cost Six-Phase Permanent Magnet Synchronous Generator for Direct-Drive Small-Scale Wind Power Application
M. E. Moazzen, S. A. Gholamian, M. Jafari-Nokandi,
Volume 13, Issue 2 (June 2017)
Abstract

Permanent magnet synchronous generators (PMSG) have a huge potential for direct-drive wind power applications. Therefore, optimal design of these generators is necessary to maximize their efficiency and to reduce their manufacturing cost and total volume. In this paper, an optimal design of a six-phase 3.5 KW direct-drive PMSG to generate electricity for domestic needs is performed. The aim of optimal design is to reduce the manufacturing cost, losses and total volume of PMSG. To find the best design, single/multi-objective design optimization is carried out. Cuckoo optimization algorithm (COA) is adopted to solve the optimization problem. Comparison between the results of the single-objective and multi-objective models shows that simultaneous optimization of manufacturing cost, losses and total volume leads to more suitable design for PMSG. Finally, finite-element method (FEM) is employed to validate the optimal design, which show a good agreement between the theoretical work and simulation results.


Regulatory Impacts on Distributed Generation and Upstream Transmission Substation Expansion Planning: A Novel Stochastic Bi-level Model
F. Misaghi, T. Barforoushi, M. Jafari-Nokandi,
Volume 13, Issue 2 (June 2017)
Abstract

In this paper, a novel framework is proposed to study impacts of regulatory incentive on distributed generation (DG) investment in sub-transmission substations, as well as upgrading of upstream transmission substations. Both conventional and wind power technologies are considered here. Investment incentives are fuel cost, firm contracts, capacity payment and investment subsidy relating to wind power. The problem is modelled as a bi-level stochastic optimization problem, where the upper level consists of investor's decisions maximizing its own profit. Both market clearing and decision on upgrading of transmission substation aiming at minimizing the total cost are considered in the lower level. Due to non-convexity of the lower level and impossibility of converting to single level problem (i.e. mathematical programming with equilibrium constraints (MPEC)), an algorithm combing enumeration and mathematical optimization is used to tackle with the non-convexity. For each upgrading strategy of substations, a stochastic MPEC, converted to a mixed integer linear programming (MILP) is solved. The proposed model is examined on a six-bus and an actual network. Numerical studies confirm that the proposed model can be used for analysing investment behaviour of DGs and substation expansion.


Enhancement of Power Quality in Grid Integrated System using DC-link Voltage PI Controlled VSC based Statcom
P. Lakshman Naik, H. Jafari, T. Sudhakar Babu, A. Anil, S. Venkata Padmavathi, D. Nazarpour,
Volume 19, Issue 2 (June 2023)
Abstract
This paper demonstrates an enhancement of power quality in grid integrated systems with the help of the proposed control strategy for voltage source converter based active power filters. The Shunt Active Power filters (SAPF) are extensively utilized in modern grid integrated systems to diminish the power quality concerns associated with it. The SAPF is one of the various power filters, which has better dynamic performance. The SAPF requires an accurate control strategy that provides robust performance under source and loads unbalance conditions. The proposed control scheme is responsible for generating the gate signals to activate the operation of Voltage Source Converter (VSC) based Active Power Filter. Thus, the performance of mitigation of harmonics of source current principally depends on the adopted algorithm. The present paper represents a performance study of a control scheme to mitigate power quality issues in the grid integrated system. The proposed system is modelled and simulated in MATLAB-Simulink in Simpower system block set.

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© 2022 by the authors. Licensee IUST, Tehran, Iran. This is an open access journal distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) license.