: Photo-Voltaic (PV) panels, whose maximal point is called the Maximum Power Point (MPP), provide extracted electrical power. In order to effectively exploit the PV System (PVS), they must be operated within the limits of this point. Later, it depends on the impedance of the connected load and on the Characteristic Impedance of the PV (CIPV) panel that varies with different climatic conditions. In a well-matched system, the load impedance is close to the CIPV and it operates normally at the MPP (via direct connection). Otherwise, coupling is fairly poor. The load impedance is different from the CIPV and, therefore, it requires the inclusion of MPP Tracking (MPPT) and a DC/DC converter as an adaptive load. In this paper, a new MPPT method based on CIPV matching is proposed. The algorithm structure is simple and easy to implement. This study focuses on how the PVS, tested and evaluated under varying load and climatic conditions, operates with the proposed MPPT controller. The present approach is characterized by a stable oscillation, with a slight fluctuation around the MPP. The controller integrates a variable step-size control and provides a rapid and precise convergence to the MPP. The simulation and experimental results prove the efficiency of the proposed method.

This paper proposes a simulator for a Photo-Voltaic (PV) generator that can reproduce the I-V and P-V characteristics of a PV cell at different high desired levels. The simulator is based on electronic components, an electronic load, a feedback controller, a source of electrical energy giving the necessary power, and a PV cell or its equivalent electrical model that serves as a PV reference. This latter, connected to the electronic load, forms the basis of the simulator. Any variation in the load impedance connected to the simulator is reflected by a variation in the electronic load impedance and will fix the PV reference operating point (Vref, Iref). Voltage Vref and current Iref of this latter point are amplified linearly and give an operating point (V, I). The latter should be adjusted in a linear gain variation with the feedback controller and fixed on the PV panel characteristic curves. Therefore, in this state, a linear gain variation in I, V or both gives as much high power as that of a serial setting and / or a parallel one (of PV modules). Using this simulator, it is possible to emulate all the characteristics of any solar PV in connection with the climatic conditions, or independently of these conditions when an electrical model is used as a reference. With the ISIS design environment, both the PV reference and the generated PV simulator are simulated to get their characteristics. The experiments are carried out under different operating conditions, and the obtained results are in good agreement with those of any PV panel.

The use of wind energy for electric power generation provides a clean and renewable source. Therefore there is an increasing interest in developing and exploiting natural energy generation system. Switched reluctance generators (SRGs) have the potential to be a robust and highly efficient electrical conversion system for variable-speed wind applications. This study presents a new approach for optimising performance of a SRG intended for variable-speed direct drive wind turbine applications. DC bus voltage level and phase voltage switching angles have been identified as control variables affecting power generation. Owing to highly non-linear characteristics of SRG, iterative simulation of the generator model on the range of control variables can be used for finding output power profile. Since it is a multidimensional search space, the number of iterations is very big. Differential evolution (DE) strategy has been introduced to find optimal firing angles and DC bus voltage level under multiple operating conditions. Optimisation of the control variables is performed using a machine model based on the measured characteristics. Selected operating points are experimentally tested using a 4 kW 1500 rpm SRG prototype. DE algorithm is a viable alternative for generating optimal control in multidimensional optimisation of SRG wind energy generation.

The simple structure, low manufacturing cost, rugged behavior, high torque per unit volume, and wide torque-speed range make a switched reluctance motor (SRM) very attractive for industrial applications. However, these advantages are overshadowed by its inherent high torque ripple, acoustic noise, and difficulty to control. The controlled parameters in SRM drives can be selected as the turn-on angle, the turn-off angle, and the current reference. This paper investigates the problem of optimal control parameters considering the maximum average torque, minimum copper losses, and minimum torque ripple as the main objectives in SRM drives. The use of evolutionary algorithms (EAs) to solve problems with multiple objectives has attracted much attention recently. Differential evolution (DE) is an EA that was developed to handle optimization problems over continuous domains. A multiobjective DE (MODE) technique is introduced here to find the optimal firing angles under multiple operating conditions. The simulation results carried out on a 4-phase 8/6 pole SRM show that the proposed MODE can be a reliable alternative for generating optimal control in the multiobjective optimization of SRM drive systems.

Programmed PWM techniques are some of the control methods used in voltage/current source converters. However, challenges are the task of defining and solving a set of nonlinear transcendental equations in order to obtain the switching angles. The paper presents an efficient Differential Evolution (DE) algorithm that significantly reduces the computational burden resulting in a fast convergence. The design procedure of a Programmed Pulse Width Modulation (PPWM) rectifier using Matlab/Simulink Blockset and code generation tools for Microchip dsPIC Digital Signal Controller (DSC) is also presented. The proposed approach follows the standard practice to utilize Matlab/Simulink and related toolboxes as the design framework to develop a rapid prototype system in a reliable procedure. The design procedure uses Simulink model of the AC-DC converter system, drive circuitry, Matlab Real-Time Workshop, and Microchip MPLAB IDE development tools. The generated and self-developed codes on dsPIC 30F4013 are tested with the dsPICDEM 2 Development Board. The output rectifier waveform and spectrum results from simulation and experimental DSC PPWM are presented.

Recently, the advances of the Internet concept and the existence of the high-speed networks as low-cost commodity components are changing the way we use popular computers today and active research area has given the emergence of a new paradigm identified by the concept of grid computing system and the Heterogeneous Processors Scheduling Problem (HPSP). The HPSP is a fundamental step for mapping a set of jobs to computational device processors. The main objective is to minimize the completion time noted makespan of the given HPSP while effectively using the computational resource processors. The type of scheduling problem is NP-hard, thus effective heuristic methods are necessary to provide a qualitative scheduling solution. In this paper, we introduce an extension of the Ant System metaheuristic that combines the MAX-MIN Ant System and Crossover Procedure concept. Indeed, at the saturation of the pheromones trail the Crossover Procedure is applied automatically to diversify the space research and improve the Ant System solution and to update the pheromone trail. In fact , we propose a hybrid metaheuristics for the Heterogeneous Processors Scheduling Problem. A 32-Jobs/4-Processors example shows the effectiveness of the developed method.

Programmed pulse width modulation (PPWM) techniques require the solution of a set of nonlinear transcendental equations in order to obtain the switching angles. The main problem of almost all of them is solving these complex equations. Normally iterative methods such as Conjugate Gradient Descent Method and Newton-Raphson Method are used to solve these equations. To obtain convergence with numerical techniques, the initial values of the variables must be selected considerably close to the exact solution. Also In most cases only a local minimum can be obtained after considerable computational time. In this paper, a variant of differential evolution algorithm (DEA) is used to find the switching angles of a PPWM controlled inverter in a way that selected harmonics are removed from its output and the magnitude of fundamental is set at any desired level. The output waveform and spectrum results from simulation and experimental Digital Signal Controller (dsPic) PPWM inverter are presented to confirm the effectiveness of the proposed Weighted Differential Evolution (W-DE) method.

The paper presents one alternative method to the conventional PWM control that provides high performance at low speed. The new developed control concept can significantly accomplish the performance of the SRM in terms of efficiency, torque ripple and power quality when compared to standard PWM current control. This control consists of feeding each phase with a constant volt per hertz (V/f) law for low speed range. The suggested V/f method is simple and is easy for practical implementation. Principle of this mode of control and analytical expressions for current calculation are provided and discussed. Obtained simulation results demonstrate the effectiveness of the proposed control strategy.

In recent years, the static and the dynamic jobs scheduling onto heterogeneous processors present a very well studied problem. Typically the Data Grid Scheduling problem (DGS) has recently become an active research area. The heterogeneous processors scheduling problem (HPSP) can be formulated in several ways and the efficient scheduling of the HPSP on the available resources is one of the key factors for achieving high performance results. Historically, finding an optimal schedule was an NP-hard problem in practical cases; researchers have resorted to devising efficient Heuristics and methods inspired by Nature's Laws. Moreover, the multi-objective scheduling research derives its importance from the need to address the real world of the heterogeneous processors application, which rarely has a single objective function. A schedule that is of a high-quality for one objective function may in fact be quite insignificant for another. Decision makers must carefully evaluate the compromise involved in considering several different criteria in practical scheduling applications. In this paper, we introduce a new hybrid approach that combines ant system optimisation and fuzzy logic concept to facilitate the multi-objective HPSP optimisation, such as the makspean, and the processors workload. Based on the concept of the ant system and fuzzy controller, we automatically control the ant system parameters evolution for the multi-objective HPSP optimisation.The simulation results indicate that the combination of the ant system approach and the fuzzy controller is not only an efficient metaheuristic tool when we search a nnulti-objective schedules under constraints but also significantly surpasses other scheduling approaches in terms of quality and solution cost.

This paper develops a new command strategy, ensuring the extension of the maximum power region of Doubly-Salient Variable Reluctance Machines when the phase switching control angles reach their limits. This new mode is often called Incomplete Demagnetization Operating Mode. The interest of this methodology is that the current in phase of demagnetization does not come back to zero. A new control parameter corresponding to minimum current is introduced when the optimization of the maximum possible power operation of the doubly-salient SRM. This concept is applicable to the full wave mode feeding.