Iranian Journal of Power Engineering
Volume:1 Issue: 1, Spring-Summer 2016

As one of the most promising Distributed Generation (DG) sources, wind power technology has been widely developed in recent years. Doubly fed induction generator (DFIG) is currently employed as one of the most common topologies for wind turbine generators (WTGs). This generator operates as a synchronous/asynchronous hybrid generators. Therefore, it is necessary to power engineers find understand the characteristics of the DFIG better. This paper presents an analytical method for analysis of large-disturbance stability of DFIG. The proposed method is based on the concepts of stable and unstable electrical-mechanical equilibrium points, the electrical-mechanical torque versus rotor speed and Critical fault clearance time of DFIG. The results of analysis specify the effective parameters on the large-disturbance stability of DFIG too. By using this method ones can reduce the simulation efforts necessary to assess the large-disturbance stability of DFIG.

In this paper, a novel method is developed for designing the output feedback controller for Static Synchronous Series Compensator (SSSC). In the proposed method, the problem of selecting the output feedback gains for the SSSC controllers is changed into an optimization problem with a time domain-based objective function.Then, it is solved by using the particle swarm optimization (PSO) algorithm that has a strong ability to find the most optimistic results. Only local and available state variables are used as the input signals of each controller for the decentralized design. Therefore, the designed SSSC controller has a simple and easy-to-implement structure. The performance of the proposed controllers is evaluated for both single-machine infinite-bus (SMIB) power system and multi-machine power system. Then, to show the robustness and effectiveness of proposed design approach, the results are presented over a wide variety of system configurations, loading conditions, and disturbances. Analyzing the results reveals that the designed PSO-based output feedback SSSC damping controller has a strong ability in damping power system oscillations. Furthermore, analyzing system performance under different operating conditions shows that the ψ-based controller is superior to the m-based controllers.

This paper presents a control strategy for fuel cell/energy storage power generation system during voltage sag conditions. The hybrid DC power sources are connected to grid using power electronic converters include DC-DC converter and grid connected voltage source inverter. The power from hybrid power sources is controlled during voltage sag by designing of control strategy for DC-DC converter. Moreover, a robust control strategy of voltage source converter for both positive and negative symmetrical components is presented to control of inverter current under unbalanced voltage sag. Simulation results for 25 KW PEM fuel cell of TALEGHAN site are given to show the response of system under voltage sag and illustrate the performance including active power control and voltage sag ride-through capability of the proposed control strategy.

In this paper, a DC-DC resonant converter with high voltage gain and small size is studied. To reduce the size and weight of this converter, the operating frequency should be as high as possible. In this research, the frequency changes from 120 to 200 kHz. Due to the high operating frequency, it is necessary to reduce the switching losses using soft switching methods. Resonant converters are suitable choice for this purpose. Since the output voltage is high, the series structure can be a good choice.

In recent years, wind energy has a remarkable growth in the world, but one of the important problems of power generated from wind is its uncertainty and corresponding power. For solving this problem, some approaches have been presented. Recently, the Artificial Neural Networks (ANN) as a heuristic method has more applications for this propose. In this paper, short-term (1 hour) and mid-term (24 hours) power forecasting are presented for a sample wind power plant by multilayer ANN. The needed inputs data are temperature and wind speed for forecasting the power. A case study has presented.

Using electric vehicles, in addition to decreasing the environmental concerns, can play an important role in decreasing the peak and filling the off-peaks of the daily load characteristics. In other words, in smart grids' infrastructure, the load characteristics can be improved by scheduling the charge and discharge process of electric vehicles. In smart grids, the customers are instantaneously informed about the load and its price and are able to react to the prices. This reaction pattern results in a wide range of changes in the load curve of the network. In this paper, a multi-stage model based on neural networks and the neuro-fuzzy network is presented for forecasting the daily electric load in the price-responsive environment of smart grids. Then, in order to determine the load and generation models of the set of electric vehicles based on the forecasted load for the next day, a complete probabilistic model of these vehicles in the range of parking lots is presented by considering three utilization strategies. These utilization strategies are: Uncontrolled Charging Mode (UCM), Controlled Charging Mode (CCM) and Smart Charge/Discharge Mode (SCDM). Finally, the proposed model is applied on the data of a target day in 2015 in NSW region of Australia's National Electricity Market and the charge and discharge schedule of electric vehicles are determined based on the forecasted load for the next day. The results indicate the most improvement in the daily load factor when the SCDM utilization strategy is employed.

This paper presents a grid connected photovoltaic system, which acts as both power generator and active power filter (APF), based on Flying Capacitor Multicell (FCM) converter. Increase in the number of output voltage levels, natural self-balancing of flying capacitors and dc link voltage and lower power rating of components are the main futures of FCM converter compared with conventional multilevel converters. Furthermore, in this paper a new control method based on instantaneous reactive power (IRP) theory and Predictive Current Control using modified phase shifted sinusoidal PWM modulation method has been presented and applied to proposed APF. Also, using a simple method for maximum power point tracking (MPPT), maximum available power of PV array has been injected to system. Finally, the control strategy and the whole system is simulated by PSCAD/EMTDC software and results are presented to validate the performance and advantages of proposed system as well as its control strategy.