This papers deal with a new Adaptive Direct Power Control for Doubly-Fed Induction Generator of 1.5 MW. The main feature of the proposed strategy is based on the replacement of the fixed switching table by an adaptive one. The online update of the adaptive switching table depends on the reactive power variation and past switching sequences. The proposed adaptive direct power control is compared with Vector Control and Classical Direct Power Control. The robustness of the proposed control scheme against parameter, load and wind speed variations have done with success. The main performance of the Adaptive Direct Power Control strategy is the reduction of powers ripples, thus reduce of torque ripple on the shaft of the turbine.

A new equivalent model of the induction motor with turn to turn fault on one phase has been developed. This model has been used to establish two schemes to estimate the severity of the short circuit fault. In the first scheme, the faulty model is considered as an observer, where a correction of an error between the measured and the estimated currents is the kernel of the fault severity estimator. However, to develop the second method, the model was required only in the training process of an artificial neural network (ANN). Since stator faults have a signature on symmetrical components of phase currents, the magnitudes and angles of these components were used with the mean speed value as inputs of the ANN

The problem of setting and coordination of Directional Over-Current Relay (DOCR) is a highly constrained optimization problem that has been solved as a linear programming problem. The calculation of the time dial setting (TDS) and pick up current (I P) setting of the relays is the core of the coordination. This paper calculates the TDS by choosing one of the available pick up current settings as the predetermined value, in this paper it will be set at 0.5, 1 and 1.5. The LP Dual simplex method is used to determine the optional TDS of the relays in compensated system by series FACTS devises ie Thyristor Controlled Series Capacitor (TCSC). A sample system of IEEE 33 bus distribution system is used to demonstrate the feasibility and efficiency of the developed method.

The present paper deals with a real-time implementation of a novel Fuzzy logic energy management strategy (EMS), applied to a battery–super capacitor hybrid energy system and associated with a permanent magnet synchronous motor (PMSM) which emulates the traction part of an electric vehicle (EV). On the sources side, the fuzzy logic supervisor acts in a smart way to permute smoothly between the various operations modes via an efficient power frequency splitting. In addition, it permits a quite regulation of both the DC bus and the super-capacitor (SC) voltages regardless of the speed profile variations to ensure an optimal power flow to the load and to keep the SC operation in a safe voltage range while providing or absorbing power in transients. On the traction side, a second order sliding mode control called ‘super-twisting’ (ST), associated with a space vector modulation (SVM) strategy is applied to ensure …

The present paper deals with a real-time assessment of a fuzzy –backstepping based control applied to a battery-supercapacitor (SC) hybrid energy storage system (HESS). To properly emulate the behavior of an electric vehicle, the proposed topology is extended to a PMSM drive, that represents the traction part. The proposed control scheme is divided into two parts: The first part plans a fuzzy logic power management approach, to operate the system in a smart way: First, It ensures an optimal load power-sharing, focusing the operation of the involved sources in a safe mode. Second, a quite regulation of both the dc bus and the SC voltage without additional controllers. The second part proposes a back-stepping direct torque control (BS-DTC), associated to a space vector modulation (SVM) strategy, to ensure decoupled torque and flux control of the PMSM machine. The experimental results, conducted on a small …

The smart grid system is key to the new electrical network infrastructure. It takes into account the use of the new information and communication technologies (ITC) and the integration of the renewable energy power generation (photovoltaics PV, concentrated solar power CSP, wind, etc). The smart grid promises better management and control of energy sources. The application of the smart grid, especially, in Algeria allows the optimal control of the electricity demand since the latter keeps rising continuously. The use of smart grid allows the rationalization of the electricity consumption in smart homes through appliance automated control. Input energy savings result in the reduction of c emission. Herein, we present a new energy management strategy tested in an experimental smart home (SM). The implemented management approach was made possible by using a new electronic system that allowed the control of all appliances via the internet network. For this purpose, a dynamic monitoring web interface was developed under an open source platform in order to process the whole data delivered by the system. The final output of the system which consists of a balance between all types of energy involved, including CO₂ gas emission, is displayed. It is only then that the user can take adequate decision and establish the priorities for rational use of the energy available.

In this paper, the method for the nonlinear control design of a permanent magnet synchronous generator based-wind energy conversion system (WECS) is proposed in order to obtain robustness against disturbances and harvest a maximum power from a typical stochastic wind environment. The technique overcomes both the problem of nonlinearity and the uncertainty of the parameter compared to such classical control designs based on traditional control techniques. The method is based on the differential geometric feedback linearization technique (DGT) and the Lyapunov theory. The results obtained show the effectiveness and performance of the proposed approach.

In this paper, a robust active fault tolerant control (AFTC) scheme is proposed for induction motor drives (IMD) via input-output linearization control (IOLC) and nonlinear observer. In order to estimate the states and to reconstruct the faults, two different observers are used; a Luenberger observer (LO) and an extended kalman filter (EKF). Further we introduce feedback linearization strategy by choosing the output function as the rotor speed and flux square. To provide a direct comparison between these FTCs schemes, the performance is evaluated using the control of IMD under failures, variable speed, and variable parameters, finally the obtained results show that the proposed controller with the proposed observers provides a good trajectory tracking, and these schemes are robust with respect to faults, parameter variations, and external load disturbances for induction motor drive system.

BLEVE is one of major accidents observed in gas industry causing severe damage to people and environment. Its effects are manifested in three ways: shock wave propagation, fireball radiation and fragments projection. To assess these effects, risk decision-makers often use Quantitative Risk Analysis (QRA). In most cases, QRA data are obtained from empirical correlations. However, these correlations are not very satisfactory because they generally overestimate BLEVE effects and do not take into account geometry effects. In order to overcome the limitations of these empirical approaches, CFD modeling appears as a powerful tool able to provide more accurate data to better realize QRA. In this paper, the objective is to develop a CFD methodology in order to predict BLEVE thermal effects. Numerical simulations are carried out using the CFD code FDS. A sensitivity analysis of numerical models is performed in order to choose the right parameters allowing to model the fireball dynamics. The models retained are based on a single-step combustion using EDC model coupled with a LES turbulence model. Predictions show good agreement in comparison with results issued from three large-scale experiments. Furthermore, a case study on a propane accumulator in an Algerian gas processing unit is carried out.