SUMMARY Higher penetration of distributed generation in distribution systems makes the islanding operation more realistic. In this paper, an adequacy assessment is presented in the presence of wind energy sources in distribution system for an islanded area. Wind speed simulation is performed using auto‐regressive moving average time series. For adequacy assessment, well‐being indices are introduced and calculated for an islanded area through an islanding algorithm. Then, sensitivity analysis is conducted to investigate the dependency of well‐being indices on key parameters of analysis. Finally, the results are presented and discussed. Copyright © 2012 John Wiley & Sons, Ltd.

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The increasing contribution of wind turbine generators (WTGs) in power grids requires the control of wind generators and their impacts on the load frequency control (LFC). In this study, a detailed strategy for the control of WTGs in a smart power grid for LFC is presented. The WTGs are controlled by applying fuzzy logic controller with three inputs from wind velocity, frequency deviations, and wind velocity changes per second. The control takes into account for each WTG, an improved pitch angle controller to assist in fast damping of frequency deviations due to sudden high wind. Also, a feedback signal from frequency deviations, with the participation factor determined by a smart learning-based intelligent controller (BELBIC) is used to determine rotor speed deviations. The controller facilitates frequency stability, and lower variations in the output power of conventional units. Simulation results, performed on a test system with three interconnected zones, validate the effectiveness of the proposed control strategy.

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Abstract:The purpose of this paper is to propose a novel design for the transverse flux permanent magnet (TFPM) disk-rotor generator with E and I-shaped cores (TFPMDEIG). Disk-shape structure increases the machine's power factor, allows for high rotational speeds, decreases centrifugal force over permanent magnets, and is employed in wind turbines, due to its compact structures. As for other advantages for this structure, one can point to the fact that there are as many windings as machine's pole pairs; these windings become parallel by observing the polarity. In other words, the total power of this machine is distributed between pole pairs, increasing the overall reliability of the machine. In this paper, first, the initial design algorithm and the basic formulas governing the behavior of the proposed structure using the equivalent magnetic circuit for each pole are provided, and the three-dimensional finite element method (3D-FEM) is used for verification of the algorithm. To validate the simulation results (3D-FEM), then, a prototype has been fabricated and experienced. The experimental results are in good agreement with simulation results.

Nowadays, regarding high percentage of wind power penetration in power systems, operating conditions of power system necessitates wind turbine generators (WTGs) to contribute in frequency regulation of the system, similar to the conventional units. To reach this goal, active power output of WTGs must be controlled, but this issue distances the operating conditions of WTGs from maximum power point tracking (MPPT) mode. This paper initially presents a completed model of doubly fed induction generator (DFIG) for dynamic studies in frequency stability analysis. Next, a coordinated control strategy to regulate active power command set point (Pcmd) for individual WTGs in a wind farm (WF) and a control strategy to regulate wind power output of DFIG upon operator's request is presented. Stability is assured under different wind conditions in the proposed control strategy. Individual WTGs set point allocation is performed applying fuzzy logic controller (FLC), while emotional learning based intelligent controller is used in regulation of the coefficient in the DFIG to reach the best stability conditions. Simulation results, performed on a test system consisting of both conventional units and WTGs, validate the effectiveness of the proposed control strategy in comparison with other mentioned solutions.

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