فهرست مطالب m. banejad

In this paper, a new dual-stator axial field flux-switching permanent magnet (DSAFFSPM) motor has been proposed to improve the torque density and cost of the machine. In this topology, the 12-pole dual-stator has been located on both sides of one 10-pole inner-toothed rotor. The dual-stator has hosted permanent magnet (PM) type of Bar-PM and the coils. The novelty of this study is development of a technique that can be implemented on PM of the DSAFFSPM structure. In this regard, the proposed analytical design with a sizing equation has been presented and multi-objective optimization is employed to achieve the optimum size by Multi-Objective Genetic Algorithm (MOGA) method. The machine characteristics are acquired and analyzed utilizing the 3D finite element method (3D-FEM). A comparative study has been done to prove the superiority of the performance indices. This topology demonstrates the high-power density and the low vibration and noise due to lower torque ripple and cogging torque. Meanwhile, the Bar-PM topology has lower core loss and thermal stress due to high-efficiency. Consequently, the proposed model provides high torque density and low cost, specifically designed for electric vehicle (EVs) applications.

This paper proposes a novel control strategy of an islanded microgrid based on virtual flux droop (VFD) control. In the conventional VFD method, the direct flux control (DFC) technique is used to generate the switching signals using the hysteresis regulators and a switching look-up table. Therefore, the voltage and the current ripples are inevitable. Moreover, as a single switching vector is applied in each control period and none of the switching vectors can produce the desired voltage, the desired dynamic performance is not achieved. Here, a novel direct flux fuzzy control (DFFC) technique is proposed to choose the best switching vector based on fuzzy logic. Furthermore, only a fraction of the control period is allocated to the appropriate active switching vector which is selected by the DFFC technique whereas the rest of the time is allocated to a null vector. The duty cycle of the selected active switching vector is optimized using a simple and robust mechanism. In order to evaluate the performance of the proposed method, an islanded microgrid and the proposed control strategy is simulated in Matlab/Simulink software. The results prove that the dynamic performance response is improved and the demanded load power is proportionately shared between the sources, while the voltage and current ripples are significantly reduced

The penetration level of the photovoltaic (PV) systems is growing in the distribution networks throughout the world. On the other hand, the voltage drop across the feeder and the voltage imbalance are important issues in radial distribution networks. One of the most effective methods to deal with these problems is reactive power injection by PV-based multiple distributed static compensators (D-Statcom). Hence, a method based on the integral to droop line algorithm, which can regulate the reactive current injection for the voltage control by optimizing the droop coefficient and integral gain, has been proposed in this paper. Therefore, genetic algorithm (GA) is used to minimize the voltage deviation (VD) and voltage unbalanced factor (VUF). The proposed method has been simulated and evaluated on the typical low voltage (LV) 3-phase distribution network. The results indicate that the voltage profile along the feeder has been improved from a poor range to the acceptable range of 0.95 to 1.05, and therefore VUF’s reach to under 0.15. Hence, optimal use of PV-Dstatcom’s capacity and validity of the mentioned method are obtained.