Mehdi Farasat

Indirect Matrix Converters as Generator–Grid Interfaces for Wind Energy Systems

Switched-inductor and quasi-Z-source indirect matrix converters are proposed as generator-grid interface for wind energy systems. Voltage levels of gearless ac generators typical for such systems are low. Thus, power electronic interfaces linking the generator with the grid must provide significant voltage boost. Switched-inductor Z-source network employs a brief shoot-through state to boost the voltage of inverters. The quasi-Z-source network offers other advantages, such as lower component ratings, reduced source stress and switch count, and simpler control strategies. The generator-grid interfaces described in this paper are based on the ultrasparse matrix topology characterized by the minimum number of semiconductor switches. The boosting networks are located between the front-end rectifier and back-end inverter. A space vector modulation technique has been developed to achieve high boosting flexibility and minimum switching losses in the converter. The fast Fourier transform analysis for the input/output currents of the converters with respect to the boost factor is carried out. The simulation and experimental results verify the effectiveness of the proposed topologies and control strategies in providing high boosting capability, while the input/output current quality is maintained within an acceptable range.

Improved model predictive current control of permanent magnet synchronous machines with fuzzy based duty cycle control

Model predictive current control uses a model of the machine and an appropriate cost function to indirectly control electromagnetic torque and reactive power. However, due to sensitivity of model predictive control (MPC) to system parameters, need for high sampling frequency, and high torque and flux ripples, this method is not employed in a wide variety of commercial drives. Incorporating the concept of duty cycle and applying two voltage vectors during a sampling period can reduce the torque and stator current ripples of a model predicative current controlled synchronous machine. In this paper, duty cycles of the voltage vectors are determined effectively using a fuzzy logic modulator. In addition, a full order Luenberger observer is designed for accurate estimation of motor variables in presence of parameter uncertainties. Matlab and real-time simulation results confirm the effectiveness of the proposed MPC.

Modeling, analysis and design of an undersea storage system

This paper presents the modeling, performance analysis, and design of an undersea storage system (USS). The USS can be employed for conditioning the output power of wave energy converters (WECs) and floating wind turbines (FWTs) at sea or ocean cites. A mathematical model is developed to describe the governing equations of the USS operation. Next, based on the developed model, a storage system is designed for a 3 MW direct drive WEC. Finally, some guidelines and discussions on determining the USS energy capacity, power capacity, optimum size, and installation depth are presented.

GA-based optimal power flow for microgrids with DC distribution network

Microgrids comprise a variety of distributed energy resources, energy storage devices, and loads. The majority of sources are not suitable for direct connection to the electrical network due to the characteristics of the energy produced, such as low voltage DC power from fuel cells and PV arrays or high frequency AC power from microturbines. Therefore, voltage source converters (VSCs) are required to interface them with the network. In microgrids with the DC distribution network, the DC voltage reference setting for the VSCs operating in the voltage regulator mode, and the optimal power reference settings of the remaining VSCs working in the power dispatcher mode must be pre-determined to maintain the DC voltage within desired margins. In this paper, the problem has been formulated as an optimization problem with VSCs switching and conduction losses selected as the objective function. Computational intelligence techniques, including genetic algorithm (GA) and simulated annealing (SA) based optimization methods, have been employed to solve the optimization problem. The results of the optimal power flow have been compared with a conventional power flow.

Voltage sensorless improved model predictive direct power control for three-phase grid-connected converters

Despite distinctive advantages such as fast dynamic, simple concept and ease of implementation, model predictive direct power control (MPDPC) suffers from some major drawbacks. First, in order to provide sinusoidal currents and low-ripple powers, very high sampling rates are required for MPDPC implementation. Furthermore, this method requires accurate knowledge of system parameters and its performance deteriorates in presence of parameter uncertainties. In this paper, an improved MPDPC is proposed, which features: 1) high current and power quality at low sampling frequencies, 2) less sensitivity to parameter uncertainties, particularly unknown grid inductance, and 3) voltage sensorless operation. The first and second features are achieved by incorporating the concept of switching duty cycles into the conventional MPDPC. In the proposed method, two voltage vectors are applied during a control period and their duty cycles are obtained by a fuzzy logic modulator. The proposed fuzzy logic modulator works based on the real and reactive power errors. Eventually, voltage sensorless operation is accomplished by designing a full-order observer. Thanks to voltage sensorless operation, the system volume and cost can be reduced. Through extensive hardware-in-the-loop tests, the superiority of the proposed MPDPC in comparison with two conventional MPDPCs is demonstrated.

Novel modulation schemes and switching pattern for Z-Source ultra-sparse matrix converter

The Z-Source networks are recently being employed in the matrix converters (MCs) to overcome their main drawback, which is the low voltage transfer ratio (VTR). In spite of several Z-Source topologies introduced for the direct and indirect matrix converters, some important issues such as their modulation, operational modes, existing challenges in practical implementation, the design of an optimal switching pattern, and so on, have not been fully addressed in the literature. This paper focuses on cascaded Z-Source ultra-sparse matrix converter (ZSUSMC), where the Z-Source network is inserted between the rectifier stage and inverter stage of an ultra-sparse matrix converter. Provided discussions can be extended to other indirect MC topologies, such as sparse and very-sparse MCs, though. Two space vector modulation (SVM) schemes, with and without considering the zero state in the space vector rectification, are proposed, and then, their advantages and disadvantages are discussed. In addition, an optimal switching pattern, which ensures minimum number of changes in the switches states over the entire switching period, is proposed. Hardware-in-the-loop studies are carried out and performance of the converter under the proposed modulation techniques is evaluated. The proposed modulations are compared with a recent study and its superior performance in terms of input and output currents quality is confirmed.

Implementing modulation schemes with three switching transients in a switching period on single DSP: Application to Z-source ultra-sparse matrix converter

Z-source networks have recently been employed with matrix converters (MCs) in order to address their limited voltage transfer ratio (VTR). In this paper, the space vector modulation of cascaded Z-source ultra-sparse matrix converter (ZSUSMC), where the Z-source network is inserted between the rectifier and inverter stages of an ultra-sparse matrix converter (USMC), is investigated. Digital implementation of the already existing space vector modulation (SVM) techniques for Z-source MCs is possible with a field programmable gate array (FPGA) employed along with a digital signal processor (DSP) due to occurrence of three switching transients in one control period. In this paper, an SVM scheme with an optimal switching pattern resulting in minimum number of changes in the switches states is developed. Furthermore, a novel approach for implementation of the developed modulation scheme on a single conventional DSP is proposed. Hardware-in-the-loop studies of the ZSUMC under the developed modulation scheme are carried out to verify the feasibility of the proposed implementation approach on a conventional DSP.

Grid-connected operation of direct-drive wave energy converter by using HVDC line and undersea storage system

Oscillatory nature of the ocean waves lead to intermittent power generated by the wave energy converters (WECs). As a result, WECs face a major barrier for grid integration. The recently introduced undersea storage system (USS) offers a viable solution to overcome this barrier by smoothing the WEC output power fluctuations. Another, but related, issue is that since the output voltage of WECs are relatively at the low-voltage range and they are deployed far away from the coast, the internal grid in wave farm is required to collect the produced energy by all WECs and deliver it to a high-voltage grid via a voltage step-up equipment. In this paper, a modular multi-level converter (MMC)-based isolated dc/dc converter is proposed for voltage step-up at the collecting point and transferring the harvested power to a high-voltage dc (HVDC) line. Simulation studies of a grid-connected direct-drive WEC along with the USS are carried out. The considered WEC is interfaced with the MMC-based converter by an ac/dc converter. The USS is employed to regulate the dc-link voltage of the MMC converter and WEC output power fluctuations. The regulated dc power is transferred through an HVDC line and converted to ac on the onshore cite.

A Time and Energy Efficient Routing Algorithm for Electric Vehicles Based on Historical Driving Data

A routing algorithm that leads to extended driving range and battery longevity of electric vehicles (EV) is proposed. In addition to locating the time and energy efficient routes, the proposed algorithm provides a desired speed profile to be tracked by the driver. Data mining techniques are employed for extracting the desired speed profile for the goal driver from a set of historical driving data. In order to select data with strong analogy to those of the goal drivers vehicle and driving conditions, driving and vehicle attributes are defined. The historical driving data are clustered and the class of the goal driver among clustered data is determined through classification. Eventually, the required travel time and energy consumption corresponding to historical speed profiles are evaluated and the time and/or energy efficient route along with the desired speed profile are determined. The proposed method is tested on a set of data gathered in the Warrigal project, which provides real vehicle state information. Since the consumed energy data are not available in this dataset, a detailed EV model is adopted to estimate the energy consumption. The obtained results verify the effectiveness of the proposed routing algorithm in locating the time and/or energy efficient routes.