Chouder Aissa

Université de M'sila · Electrical Engineering

Artificial bee colony (ABC) algorithm has several characteristics that make it more attractive than other bio-inspired methods. Particularly, it is simple, it uses fewer control parameters and its convergence is independent of the initial conditions. In this paper, a novel artificial bee colony based maximum power point tracking algorithm (MPPT) is...

Abstract—In this article, an improved deadbeat control algorithm suitable for digital signal processor-based circuit implementation is proposed. The control algorithm allows the derivation of a nearly sine wave output current with a fixed switching frequency of a current- controlled voltage source inverter. Two low-pass output filters con- figurations...

String inverter PV systems with by-pass diodes require improved Global Maximum Power Point Tracking (GMPPT) algorithms to effectively reach the absolute maximum power operating point. Several GMPPT algorithms have been proposed to deal with this problem, but most of them require scanning wide voltage ranges of the PV array from nearly zero voltage...

In this work, we present a new automatic supervision and fault detection procedure for PV systems, based on the power losses analysis. This automatic supervision system has been developed in Matlab&Simulink environment. It includes parameter extraction techniques to calculate main PV system parameters from monitoring data in real conditions of work...

This work identifies the most effective machine learning techniques and supervised learning models to estimate power output from photovoltaic (PV) plants precisely. The performance of various regression models is analyzed by harnessing experimental data, including Random Forest regressor, Support Vector regression (SVR), Multi-layer Perceptron regr...

Under the presence of nonlinear load, the most existing virtual impedance (VI) methods-based control solution performs poorly in reactive power sharing among droop-operated VSIs in microgrids (MGs). This may be due to the involved estimation techniques for extracting the current harmonics at selected frequencies, which suffer from either poor accur...

This work focuses on identifying the most effective machine learning techniques and supervised learning models to precisely estimate power output from Photovoltaic (PV) plants. The performance of various regression models is analyzed by harnessing experimental data, including Random Forest, Support Vector Regression (SVR), Multi-layer Perceptron (M...

Renewable energies have become pivotal in the global energy landscape. Their adoption is crucial for phasing out fossil fuels and promoting environmentally friendly energy solutions. In recent years, the energy management system (EMS) concept has emerged to manage the power grid. EMS optimizes electric grid operations through advanced metering, aut...

This paper presents amodel for designinga stand-alonehybrid systemconsistingof photovoltaic sources, windturbines, astoragesystem, andadieselgenerator.Theaimis todeterminetheoptimal sizetoreduce thecostofelectricityandensuretheprovisionofelectricityatlowerandmorereliablepricesforisolatedrural areas.Threescenariosforfive, fifteen,andtwentyruralhomes...

This paper introduces an enhanced single-phase phase-locked loop (PLL) system, referred to as the Super Twisting Algorithm Phase-Locked Loop (SOGI PLL-STA), built upon the foundation of Second-Order Generalized Integrator (SOGI) technological fields, commonly employed for grid synchronization in single-phase grid-connected power converters. Unlike...

In the domain of microgrid (MG) inverters, one of the most intricate challenges is orchestrating a seamless transition from the conventional grid-connected (GC) mode to the autonomous stand-alone (SA) operation mode. This transition necessitates a delicate balance to sustain the inverter's frequency and voltage parameters within specified tolerance...

Abstract Both fertility policy and the healthy development of financial markets are important topics for sustainable economic and social development. By using the difference-in-difference (DID) model, this paper investigates how the universal two-child policy (UTCP) in China aiming to improve fertility affects household financial asset allocation,...

This study presents the measured data of the "Oued Keberit" PV plant over a period of four months (January to April 2022) after nearly 6 years of outdoor exposure to the climate of Souk Ahras, eastern Algeria, in order to evaluate the performance of the solar PV system. This evaluation includes the calculation of PV system performance variables suc...

Accurate and reliable fault detection procedures are crucial for optimizing photovoltaic (PV) system performance. Establishing a trustworthy PV array model is the primary step and a vital tool for monitoring and diagnosing PV systems. This paper outlines a two-step approach for creating a reliable PV array model and implementing a fault detection p...

The paper presents an application of deep learning for fault detection in PV systems located in Algiers –Algeria which has a nominal power of 9.54 kW. Each PV array comprises 30 PV modules each string contains 15 PV modules in series. Fault detection and diagnosis of Photovoltaic Systems (PVS) is an important task for successful solar power generat...

Photovoltaic (PV)-system-generated solar energy has inconsistent and variable properties, which makes controlling electric power distribution and preserving grid stability extremely difficult. A photovoltaic (PV) system's performance is profoundly affected by the amount of sunlight that reaches the solar cell, the season of the year, the ambient te...

This paper proposes an improved fault diagnosis for stand-alone photovoltaic (SAPV) system using artificial neural network (ANN) and power loss parameters as inputs. Unlike the classical power analysis approach that fails to find precisely the fault type, this method can accurately identify the fault class and can be used in real-time applications....

This paper presents a comparison of various metaheuristic algorithms used for extracting electrical parameters from specific photovoltaic (PV) panels. The focus lies on assessing and comparing the efficiency of eight chosen algorithms in precisely deriving electrical parameters from PV modules, selected for their novelty and widespread use. The ODM...

In this paper, a deadbeat control technique for single-phase inverters used in UPS applications is presented. For the suggested control approach to maintain sinusoidal output voltage for high dynamic performance even with load fluctuations, measurements of capacitor current and output voltage are necessary. By reducing the error between the output...

During the operation of photovoltaic systems, various faults can occur and result in serious problems, such as energy loss or system shutdown. Therefore, it is crucial to identify and diagnose these faults in order to improve system performance. The purpose of this work is to propose an efficient and simple procedure for the early detection and dia...

The abrupt transfer from grid-connected (GC) to stand-alone (SA) operation modes is one of the major issues that may threaten the stability of a distributed generation (DG) system. Furthermore, if the islanding mode happens, it is vital to take into consideration the load voltages or load current waveforms as soon as feasible. This paper develops a...

Partial shading (PS) is a prevalent phenomenon that often affects photovoltaic (PV) installations , leads to the appearance of numerous peaks in the power-voltage characteristics of PV cells, caused by the uneven distribution of solar irradiance on the PV module surface, known as global and local maximum power point (GMPP and LMPP). In this paper,...

In recent years, DC microgrid systems feeding constant power loads (CPLs) have been given a particular focus due to their effect on the overall system stability caused by their electrical characteristics behaving as negative incremental impedance. To address this issue, this paper investigates the stabilization of a DC bus voltage in a DC microgrid...

The worst-case scenario in distributed generation (DG) systems is an abrupt switch from grid-connected (GC) to stand-alone (SA) modes. This must be taken into consideration to protect the integrated power system when islanding happens. In the present paper, a robust sensor-less current control based on a digital Luenberger observer has been propose...

Computation of active and reactive powers is a crucial step in droop‐controlled single‐phase voltage source inverters (VSIs) in standalone microgrid since the performance and stability of the power‐sharing strategy are strongly influenced by its speed and accuracy, especially in the case of non‐linear loads. Here, an improved performance of power‐s...

This paper presents a dead-beat control algorithm for Uninterruptible Power Supply (UPS) applications of single-phase inverters. The proposed control method requires the measurement of capacitor current and output voltage in order to keep the output voltage sinusoidal ensuring high dynamic performance even under load changes. The dead-beat controll...

Extracting the parameters of a lead‐acid battery under real‐world operating conditions is a significant part of solar photovoltaic (PV) engineering. Usually, the battery management system handles the battery system based on its model. However, its model's parameters can change due to its electrochemical nature. Hence, enhancing the model parameters...

in this paper, an ancient inspired algorithm called Giza Pyramid Construction (GPC) is used to extract the five unknown parameters in the one diode model of a PV module. The conducted investigation on the accuracy to extract the five parameters shows that GPC algorithm gives good convergence rate toward the global minimum. The obtained parameters f...

This paper studies a control of an inverter to emulate a synchronous generator (SG), which has many benefits in terms of stability. These benefits can be used in the virtual synchronous generator (VSG) and are proven experimentally in the stand-alone mode. Theoretical analysis and designs of the VSG are presented and verified by simulation in Psim....

This paper develops an advanced scheme, modelling, and analysis of power flow control intended for grid-connected droop-controlled VSIs within a single-phase microgrid (MG). The proposed control scheme includes a power calculation method based on an enhanced second-order generalized integrator frequency-locked loop (ESOGI-FLL). Contrary to the exis...

This important book fills the gap between smart photovoltaic technology and artificial intelligence technologies and is a major contribution to a growing field. Artificial Intelligence for Smart Photovoltaic Technologies provides a comprehensive introduction to these two areas and includes a description of key artificial intelligence algorithms and...

Due to its several powerful characteristics, the Grey Wolf Optimization (GWO) algorithm has recently become widely used in numerous optimization problems. In photovoltaic (PV) systems, power-voltage (P–V) curves present multiple maxima in case of partial shadow or modules mismatch which can be viewed as an optimization problem. In this paper, a GWO...

One 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 (...

This paper deals with the robust current control for three-phase Grid-Connected Inverters (GCI) of distributed generation (DG) systems based on a Super-Twisting Sliding mode controller (ST-SMC) during injecting active and reactive power into the grid. This approach is capable of decreasing the chattering phenomena and improving the system's accurac...

In a microgrid architecture that includes energy storage systems based on parallel batteries, the inequalities in the batteries’ state of charge may cause inconsistency in the residual capacity of each battery. As a consequence, the battery cells may be degraded owing to overcharging or deep discharging. This paper presents an optimized load-sharin...

This article deals with inter-turn short-circuit fault detection in stator windings of squirrel cage induction machines. The main aim is to perform harmonic analysis of different electrical signatures namely the stator phase current, external magnetic flux and electromagnetic torque at different levels of mechanical load in order to develop an effi...

The use of the electrical energy storage (EES) plays an important role in the transition of energy generation towards renewable energy sources (RESs). An effective sizing of EES systems is very important in order to cope with the volatility of RESs and to ensure a reliable energy supply. The present paper provides a methodology which helps to deter...

The amount of solar energy reaching the ground is converted to electricity using the photovoltaic conversion systems, these systems are environmentally friendly unlike to the conventional electrical power produced from fossil fuels. These optoelectronic components' functionality is frequently described by the I-V relationship's characteristic, the...

The exact parameter estimation of the fuel cell model is considered a critical stage in delivering a consistent emulation for the fuel cell system characteristics. The aim of this is to suggeste a robust methodology based on the Gradient-based Optimizer (GBO) to identify the best parameters of PEM fuel cell (PEMFC). Three distinct types of PEM fuel...

In a microgrid architecture that includes energy storage systems based on parallel batteries, the inequalities in the batteries’ state of charge may cause inconsistency in the residual capacity of each battery. As a consequence, the battery cells may be degraded owing to overcharging or deep discharging. This paper presents an optimized load-sharin...

DESCRIPTION Photovoltaic (PV) systems operating in real conditions of work are very often subject to several faults that may lower significantly the produced energy and shorten their availability. Therefore, powerful and trusted fault detection procedures are necessary to enable early maintenance and avoid excessive energy losses. The large increas...

This article proposes the modelling, detection and classification of the faults of a grid connected photovoltaic system by artificial neural networks. The validation of our study required a real meteorological data such as (Module Temperature, Solar Irradiance) as well as electrical data (Impp, Vmpp) of the month of March 2014, the system is compos...

The identification of actual photovoltaic (PV) model parameters under real operating condition is a crucial step for PV engineering. An accurate and trusted model depends mainly on the accuracy of the model parameters. In this paper, an accurate and enhanced methodology is intended for PV module parameters extraction in outdoor conditions. The prop...

Green hydrogen is undoubtedly the most promising energy vector of the future because it is captured by renewable and inexhaustible sources, such as wind and/or solar energy, and can be stored over the long in high-pressure cylinders, which can be used to feed the fuel cells to produce the electricity without emitting any pollutants. The system inco...

Battery as a critical element in the stand-alone photovoltaic system remains without an appropriate protection fuse for shortcircuit failure inside it. Therefore the safety is hreatened and the lifetime of the battery is reduced. To address this problem, supervision of battery internal short-circuit is proposed using a machine learning anomaly dete...

This paper presents an optimal parameter identification strategy of the lithium-ion (Li-ion) battery model applying a recent metaheuristic artificial ecosystem-based optimization (AEO) algorithm, which proves its ability in terms of both convergence speed and complexity. The key idea is to update the battery model parameters using the optimizer out...

Fault diagnosis has become an indispensable part of PV installations to ensure their safety and reliability. The accuracy, rapidity, specificity, sensitivity and the precision of faults detection and isolation are the most pertinent criterions of the diagnosis quality. The present work examines the impact of the Artificial Neural Networks choice on...

Fault diagnosis has become an indispensable part of PV installations to ensure their safety and reliability. The accuracy, rapidity, specificity, sensitivity and the precision of faults detection and isolation are the most pertinent criterions of the diagnosis quality. The present work examines the impact of the Artificial Neural Networks choice on...

Purpose. In last decade the problem of energy management system (EMS) for electric network has received special attention from academic researchers and electricity companies. In this paper, a new algorithm for EMS of a photovoltaic (PV) grid connected system, combined to an storage system is proposed for reducing the character of intermittence of P...

The present work brings a new intelligent algorithm for PV system's diagnosis and fault detection (IFD). At this stage of the study, this algorithm can detect and identify three recurrent cases between healthy and short circuit faults, as well as string disconnection in PV array using artificial neural networks (ANN). Both, detection and isolation...

Photovoltaic (PV) systems based on multi-string configuration are the best effective solution, given its advantages in terms of system availability, reliability and energy efficiency. In this particular configuration each sub-string has its own DC-DC converter and a dedicated maximum power search algorithm which increase the cost and complexity. In...

DC microgrids are gaining more and more popularity and are becoming a more viable alternative to AC microgrids (MGs) due to their advantages in terms of simpler power converter stages, flexible control algorithms and the absence of synchronization and reactive power. However, DC-MGs are prone to instability issues associated with the presence of no...

he need of sustainable energy solutions is a demand nowadays due to the high electricity consumption in combination with the desired environmental friendly solutions for power production development. Photovoltaic (PV) energy, which has gained a central place in the governments’ energy policies, is a promising solution to address the aforementioned...

one of the solutions to integrate the renewable energies is the DC microgrid (MG). The DC MG consists of the distributed generation (DG) units, which are responsible to integrate the renewable energies and connected in parallel to a common bus for supplying several kinds of load. The voltage difference between the DG units and the resistance lines...

In a microgrid (MG) topology, the secondary control is introduced to compensate for the voltage amplitude and frequency deviations, mainly caused by the inherent characteristics of the droop control strategy. This paper proposes an accurate approach to derive small signal models of the frequency and amplitude voltage at the point of common coupling...

For the proper operation of a microgrid, an accurate estimation of the grid parameters such as phase angle, operating frequency and amplitude under various disturbances is of prime interest. In this paper, an enhanced second-order generalized integrator-based frequency-locked loop (ESOGI-FLL) intended for DC-offset rejection in both grid-connected...

The use of a reliable model of a photovoltaic (PV) module is the main step for energy prediction and an important tool for monitoring and supervision. To this end, PV modeling primarily involves the formulation of the non-linear current versus voltage (I-V) curve. This paper presents the application of the Nelder-Mead simplex search method for iden...

There is growing interest in solar batteries, especially for photovoltaic (PV) applications. Therefore, an accurate battery model is required for the PV system because of its influence on system efficiency. Several mathematical models of batteries have been described in the scientific literature. However, this paper reviews three electrochemical mo...

Fault classification using supervised machine learning Artificial Neural Network (ANN) is proposed to diagnose some defaults in Stand-alone photovoltaic (SAPV) system, where the data learning includes the voltage and current of PV panels, Battery and load are collected for different operation mode of the system (healthy and faulty). The proposed ap...