• Energy Research

There has always been a high expectation that wind generation systems would capture maximum power and integrate properly with the grid. Utilizing a wind generation system with increased management to meet the growing electricity demand is a clever way of accomplishing this. However, wind power generation systems require a sophisticated, unique, and dependable control mechanism in order to achieve stability and efficiency. To improve the operation of the wind energy conversion method, researchers are continually addressing the obstacles that presently exist. Therefore, it is necessary to know which control can improve the whole system’s performance and ensure its successful integration into the network, despite the variable conductions. This article examines wind turbine control system techniques and controller trends related to the permanent magnet synchronous generator. It presents an overview of the most popular control strategies that have been used to control the PMSG wind power conversion system. Among others, we mention nonlinear sliding mode, direct power, backstepping and predictive currents control. First, a description of each control is presented, followed by a simulation performed in the Matlab/Simulink environment to evaluate the performance of each control in terms of reference tracking, response time, stability and the quality of the signal delivered to the network under variable wind conditions. Finally, to get a clear idea of the effect of each control, this work was concluded with a comparative study of the four controls.

AbstractIn recent years, the improvement of photovoltaic water pumping system (PVWPS) efficiency takes the considerable interest of researchers due to its operating based on cleaner electrical energy production. In this paper, a new approach based on fuzzy logic controller incorporating loss minimization technique applied to the induction machine (IM) is developed for PVWPS applications. The proposed control selects the optimal flux magnitude by minimization of the IM losses. Moreover, Variable step size perturb and observe method is introduced. The suitability of the proposed control is approved by reducing the absorbed current; therefore, the motor losses are minimized and the efficiency is improved. The proposed control strategy is compared with the method without losses minimization. The comparison results illustrate the effectiveness of the proposed method based on losses minimization regarding the electrical speed, absorbed current, flow water and developed flux. A processor-in-the-loop (PIL) test is effectuated as an experimental test of the proposed method. It consists in implementing the generated C code on the STM32F4 discovery board. The obtained results from the embedded board are similar to numerical simulation results.

AbstractOne of the major challenges in photovoltaic (PV) systems is extracting the maximum power from the PV array, especially when they operate under partial shading conditions (PSCs). To address this challenge, this paper introduces a novel hybrid maximum power point tracking (MPPT) method based on grey wolf optimization and particle swarm optimization (GWO–PSO) techniques. The developed MPPT technique not only avoids the common disadvantages of conventional MPPT techniques (such as perturb and observe (P&O) and incremental conductance) but also provides a simple and robust MPPT scheme to effectively handle partial shading in PV systems, since it requires only two control parameters, and its convergence to the global maximum power point (GMPP) is independent of the search process's initial conditions. The feasibility and effectiveness of the hybrid GWO–PSO-based MPPT method are verified via a co-simulation technique that combines MATLAB/SIMULINK and PSIM software environments, while comparing its performance against GWO, PSO and P&O based MPPT methods. The simulation results carried out under dynamic environmental conditions have shown the satisfactory effectiveness of the hybrid MPPT method in terms of tracking accuracy, convergence speed to GMPP and efficiency, compared to other methods.

This paper presents an implementation of real-time energy management systems (EMS) to maximize the efficiency of the electricity distribution in an isolated hybrid microgrid system (HMGS) containing photovoltaic modules, wind turbine, battery energy storage system, and diesel generator (DG) which is used as a backup source. These systems are making progress worldwide thanks to their respect for the environment. However, hybridization of several sources requires power flow control (PFC). For this reason, in this work, a proper energy management system is developed using LabVIEW software and embedded in a suitable platform for the real-time management of the hybrid energy system. The developed EMS is tested and validated through a small-scale application which accurately represents the case study of an isolated mosque located in a remote area of Morocco. The aim of this paper is to (i) propose a novel modelling method and real-time monitoring interface under the LabVIEW software based on the real data obtained by an optimal sizing previously made using Homer-pro software and (ii) implement the power control system on a low-consumption embedded platform that is the Raspberry-pi3.

AbstractImpacts of blending fusel oil with gasoline on fuel combustion have been investigated experimentally in the current research to evaluate engine performance improvement and exhaust emission. Tested fuel include F10, F20 (10% and 20% of fusel oil by volume) and pure gasoline as baseline fuel have been used to operate 4-cylinder SI engine at increasing engine speed and constant throttle valve of 45%. The present results reveal a shorter combustion duration and better engine performance with F10 over engine speeds with maximum value of 33.9% for the engine brake thermal efficiency. The lowest BSFC of 251 g/kW h was recorded at 3500 rpm engine speed also with F10. All blended fuel have almost similar COVIMEP. Less NOx emission was measured with F10 at 4500 engine speed compared to gasoline. However, CO emissions reduced while higher CO2 was observed with introducing fusel oil in the blend. Moreover, HC emission increased an average by 11% over speed range and the highest value was achieved with 10% fusel oil addition compared to 20% and pure gasoline. Accordingly, higher oxygen content of fusel oil and octane number contribute to improve combustion of fuel mixture.

This paper aims to research a photovoltaic solar water pumping system (PVWPS) based on a three-phase induction motor (IM) with high performance, low cost, and without chemical energy storage. The proposed control for the PVWPS consists of two principal controllers. The first controller is used to control the system to reach its maximum using a robust MPPT control strategy that is based on the Kalman filter algorithm (KF-MPPT). While the second controller is based on 12-sectors Direct Torque Control (DTC). This technique is proposed to control the IM with the centrifugal pump through a three-level inverter with a neutral point clamped (NPC) structure. Furthermore, to increase the performance of the proposed control without affecting the system efficiency, the torque and flux hysteresis regulators level is increased to five and three levels, respectively. To see the behaviors of the PVWPS with the proposed control, the whole system was designed and simulated in the MATLAB/Simulink environment. This work also includes a comparative analysis to show the performance of the proposed control compared to the conventional controls. This analysis is done first to compare the performance of the KF-MPPT, VSS-P&O-MPPT, and VSS-INC-MPPT using variable radiation, and then to compare the proposed KF-MPPT-PDTC and the conventional KF-MPPT-DTC under a daily climatic profile. The simulated results showed that PVWPS with KF-MPPT and PDTC provide a better performance in terms of reference tracking, response time, torque and flux ripple reduction, current quality, as well as water pumped.