DESIGN OF AN EFFECTIVE CONTROL FOR GRID-CONNECTED PV SYSTEM BASED ON FS-MPC

This paper is deals in part of research that has been conducted on modern means in the basis of power electronics. Harmonic cancellation of distribution network is currently a serious problem, especially in high electrical industry. The main source of harmonic currents injected into the network requires attention to reduce the current harmonic levels. Energy quality is a fairly broad concept which covers both, the quality of power supply (voltage wave) and these of the currents injected into the electrical grid. In this context, a modern approved preventive solution in purpose to limit the rate of harmonic disturbance caused by the deferent power electronics systems connected to the grid must take action. It appears necessary to develop the quality and stability of the grid and develop curative devices such as converters provided with a control device making the current drawn on the most sinusoidal network possible. This paper proposes a control of tow stage grid tied PV system established on finite set model predictive control (FS-MPC). The design of FS-MPC is developed depending on the structure and operating principle associated to three-phase inverter tied to the grid.  In this context, we have also employed the structure of MPPT controller (P&O) and PI controller for adjustment of the DC-bus voltage. To set the proposed control scheme, numerical simulations are carried out using Matlab/Simulink 2013b. The obtained results demonstrate that the proposed control scheme assure the tracking of MPP and the injection of extracted PV power into the grid with high current quality under irradiation changes

Extracting Accurate Parameters from a Proton Exchange Membrane Fuel Cell Model Using the Differential Evolution Ameliorated Meta-Heuristics Algorithm

The electrochemical proton exchange membrane fuel cell (PEMFC) is an electrical generator that utilizes a chemical reaction mechanism to produce electricity, serving as a sustainable and environmentally friendly energy source. To thoroughly analyze and develop the features and performance of a PEMFC, it is essential to use a precise model that incorporates exact parameters to effectively suit the polarization curve. In addition, parameter extraction plays a crucial role in the simulation analysis, evaluation, optimum control, and fault detection of the proton exchange membrane fuel cell (PEMFC) system. Despite the development of many algorithms for parameter extraction in PEMFC, obtaining accurate and trustworthy results rapidly remains a challenge. This study presents a hybridized algorithm, namely differential evolution ameliorated (DEA) for reliably estimating PEMFC model parameters. To evaluate the proposed DEA-based parameter identification, a comparison analysis with previously published methods is conducted using MATLAB/SimulinkTM (R2016b, MathWorks, Natick, MA, USA) in terms of system correctness and convergence process. The proposed DEA algorithm is tested to extract the parameters of two PEMFC models: SR-12 500 W and 250 W. The sum of the squared errors (SSE) between the experimental and the obtained voltage data is defined as an objective function. The simulation results prove that the suggested DEA algorithm is capable of identifying the optimal PEMFC parameters rapidly and accurately in comparison with other optimization algorithms

Design of an Intelligent Cascade Control Scheme Using a Hybrid Adaptive Neuro-Fuzzy PID Controller for the Suppression of Drill String Torsional Vibration

Eliminating the excessive stick–slip torsional vibrations of drill strings by utilizing an effective controller can significantly increase penetration rates and reduce drilling operation costs. The present study aims to develop a fast and intelligent cascade control structure for a multi-degree-of-freedom drill string system under torsional vibrations. The proposed control configuration consists of two control loops in a cascade arrangement. The first controller estimates the top drive velocity reference from the actual drill bit velocity and its reference. The role of the second controller is to regulate the top drive velocity to its reference by generating the necessary torque for the drilling operation process to progress. Each control loop is designed based on a hybrid adaptive neuro-fuzzy PID and feedforward term. The latter assures fast regulation when there are sudden changes in operation. To evaluate the performance of the suggested cascade feedforward neuro-fuzzy PID (CFF-NFPID) control structure, extensive simulations were conducted using Matlab/Simulink. The simulation results clearly showed that the proposed CFF-NFPID controller provided high-performance control with variations in the weight on the bit and the desired drill bit rotary speed in comparison with that of cascade feedforward fuzzy PID, sliding-mode, cascade feedforward PID, cascade PID, and conventional PID controllers. Furthermore, the control robustness is very suitable despite the change in the system parameters

A Robust Control of Two-Stage Grid-Tied PV Systems Employing Integral Sliding Mode Theory

This contribution considers an improved control scheme for three-phase two-stage grid-tied photovoltaic (PV) power systems based on integral sliding mode control (ISMC) theory. The proposed control scheme consists of maximum power point tracking (MPPT), DC-Link voltage regulation and grid current synchronization. A modified voltage-oriented maximum power point tracking (VO-MPPT) method based on ISMC theory is proposed for design of an enhanced MPPT under irradiation changes. Moreover, a novel DC-Link voltage controller based on ISMC theory is proposed to achieve good regulation of DC-Link voltage over its reference. To inject the generated PV power into the grid with high quality, a voltage-oriented control based on space vector modulation (SVM) and ISMC (VOC-ISMC-SVM) has been developed to control the grid current synchronization. Numerical simulations are performed in a MATLAB/SimulinkTM (R2009b, MathWorks, Natick, MA, USA) environment to evaluate the proposed control strategy. In comparison with conventional control schemes, the developed control strategy provides an accurate maximum power point (MPP) tracking with less power oscillation as well as a fast and an accurate DC-Link regulation under varying irradiation conditions. Moreover, the transfer of the extracted power into the grid is achieved with high quality

A high-performance control scheme for photovoltaic pumping system under sudden irradiance and load changes

A low-cost photovoltaic (PV) pumping system based on three phase induction motor (IM) without the use of chemical energy storage elements is presented in this paper. The PV generator-side boost converter performs the maximum power point tracking (MPPT), while the IM−side two-level inverter regulates the net DC-link voltage and the developed electromagnetic torque by IM, which is coupled with a centrifugal pump. An improved variable step size perturb and observe (P&O) algorithm is proposed to reduce the steady-state PV power fluctuation, to accelerate the tracking operation under sudden irradiance changes, and to protect IM under load drops. The proposed algorithm is based on a current control approach of the boost converter with a model predictive current controller to select the optimal control action. Moreover, predictive torque and flux control (PTC) is used to control IM drive, due to its advantages such as faster torque response, lower torque ripple, and simplicity of implementation. Furthermore, a Takagi-Sugeno (T-S) type fuzzy logic controller (FLC) is developed in order to regulate the DC-link voltage, by producing the torque reference for PTC algorithm. In order to examine and assess the performance of the proposed control scheme for PV pumping system, a complete simulation model is developed using MATLAB/SimulinkTM environment and confirmed through real-time hardware in the loop (HIL) system. The obtained results indicate the excellent performance of the proposed control scheme, which is much better than the conventional scheme based on conventional techniques (P&O algorithm and direct torque control (DTC))