Yassine Sayouti

Université Hassan II Mohammedia

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Mohamed Akherraz

Mohammed V University

Abdelmajid Badri

University of Hassan II Casablanca

Ahmed Abbou

Ecole Mohammadia d'Ingénieurs

Hassane Mahmoudi

Ecole Mohammadia d'Ingénieurs

Marouane Lagouir

University of Hassan II Casablanca

Anas Bouaouda

University of Hassan II Casablanca

Hicham Lhachimi

Université Hassan II Mohammedia

Y. El Kouari

University of Hassan II Casablanca

Mohammed Kharrich

Chungnam National University

Abdelaziz Mouhou

University of Hassan II Casablanca

Cooperative Institutions

Ecole Mohammadia d'Ingénieurs

University of Hassan II Casablanca

Mohammed V University

Université Hassan II Mohammedia

Mohamed I University

École Normale Supérieure de l'Enseignement Technique de Mohammedia

University of Pitesti

Fuzzy Systems Institute

Renewable Energy Systems (United Kingdom)

Laboratoire d'Informatique et d'Automatique pour les Systèmes

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Development of an Intelligent Energy Management System with Economic Dispatch of a Standalone Microgrid

DOAJ (DOAJ: Directory of Open Access Journals) (2019)

Marouane Lagouir Abdelmajid Badri Yassine Sayouti

Microgrid

Economic Dispatch

Energy management system

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Citations (1)

dSPACE direct torque control implementation for induction motor

2022 30th Mediterranean Conference on Control and Automation (MED) (2010)

Ahmed Abbou Yassine Sayouti Hassane Mahmoudi Mohamed Akherraz

This paper presents an dSPACE implementation of three-phase squirrel-cage induction motor control using direct torque control (DTFC) technique with the help of intelligent techniques. A fuzzy PI controller is used in the speed control loop. The classical lookup table is replaced by a neural network selector providing switching state to the inverter. The rotor speed is estimated by a simple open loop estimator. A Matlab/Simulik Simulation and DSP experimental using TMS320F240 results are shown in this paper. A good agreement between the simulation results and experimental results are achieved.

DSPACE

Squirrel-cage rotor

Lookup table

Open-loop controller

10.1109/med.2010.5547641

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Citations (8)

MRAS-ANN based sensorless speed control for direct torque controlled induction motor drive

International Conference on Power Engineering, Energy and Electrical Drives (2009)

Yassine Sayouti Ahmed Abbou Mohamed Akherraz Hassane Mahmoudi

This paper presents speed sensorless direct torque control (DTC) of induction motor using Artificial intelligence (AI). The artificial neural network (ANN) MRAS-based speed estimation is used. The error between the reference model and the neural network based adaptive model is used to adjust the weights by on-line Back propagation (BP) training algorithm. The speed loop regulation is carried out by a fuzzy controller giving exceeding performance in comparison with a classic PI regulator. The performance of fuzzy speed controller and speed estimator are investigated with the help of Matlab/Simulink®. The estimated speed accuracy was achieved with high performance of the speed controller. The estimated speed error is less than 1% both in transient and steady-state operation. The fuzzy controller is robust to load torque perturbations and speed reference changes.

MRAS

Electronic speed control

10.1109/powereng.2009.4915161

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Hybrid Meta-Heuristic Algorithms for Optimal Sizing of Hybrid Renewable Energy System: A Review of the State-of-the-Art

Archives of Computational Methods in Engineering (2022)

Anas Bouaouda Yassine Sayouti

Meta heuristic

Viewpoints

10.1007/s11831-022-09730-x

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Citations (65)

Solving Multi-Objective Energy Management of a DC Microgrid using Multi-Objective Multiverse Optimization

International Journal of Renewable Energy Development (2021)

Marouane Lagouir Abdelmajid Badri Yassine Sayouti

This paper deals with the multi-objective optimization dispatch (MOOD) problem in a DC microgrid. The aim is to formulate the MOOD to simultaneously minimize the operating cost, pollutant emission level of (NOx, SO2 and CO2) and the power loss of conversion devices. Taking into account the equality and inequality constraints of the system. Two approaches have been adopted to solve the MOOD issue. The scalarization approach is first introduced, which combines the weighted sum method with price penalty factor to aggregate objective functions and obtain Pareto optimal solutions. Whilst, the Pareto approach is based on the implementation of evolutionary multi-objective optimization solution. Single and multi-objective versions of multi-verse optimizer algorithm are, respectively, employed in both approaches to handle the MOOD. For each time step, a fuzzy set theory is selected to find the best compromise solution in the Pareto optimal set. The simulation results reveal that the Pareto approach achieves the best performances with a considerable decrease of 28.96 $/day in the daily operating cost, a slight reduction in the power loss of conversion devices from 419.79 kWh to 419.29 kWh, and in less computational time. While, it is noticing a small increment in the pollutant emission level from 11.54 kg/day to 12.21 kg/day, for the daily microgrid operation. This deviation can be fully covered when comparing the cost related to the treatment of these pollutants, which is only 5.55 $/day, to the significant reduction in the operating cost obtained using the Pareto approach.

Microgrid

10.14710/ijred.2021.38909

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Citations (4)

Microgrid Sizing with Environmental and Economic Optimization

Mohammed Kharrich Yassine Sayouti Mohamed Akherraz

Hybrid microgrid is the best system to build for the lower demand mainly in the non-electrified rural area. However, a hybrid system based on PV, wind turbine, diesel and Battery Energy Storage System (BESS) must be optimized. In this paper, Multi-Objective Particle Swarm Optimization (MOPSO) method is used to design the hybrid system. Net Present Cost (NPC) that cover all capital, operation maintenance and replacement cost, and emission cost to evaluate the damage caused by the pollution are the choosen obective functions. Two location area are considered to sizing the hybrid system taking in account reliability with Loss of Power Supply Probability (LPSP), Fraction Renewable (FR) that must be upper to 90% and availability should be upper to 96%. A Pareto-optimal solution using Pareto frontier give the best results with highest reliability and availability of this system.

Microgrid

Diesel generator

10.1109/repsgie.2018.8488864

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Citations (13)

On-Line Neural Network Stator Resistance Estimation in Direct Torque Controlled Induction Motor Drive

Yassine Sayouti Ahmed Abbou Mohamed Akherraz Hassane Mahmoudi

This paper presents an on-line estimation for the stator resistances of the induction motor in the direct torque controlled drive, using artificial neural networks. The variation of stator resistance due to changes in temperature or frequency degrades the performance of such control strategy. In order to solve this issue, a backpropagation algorithm is used for training of the neural network. The error between the desired state variable of an induction motor and the actual state variable of a neural model is back propagated to adjust the weights of the neural model, so that the actual state variable tracks the desired value. Simulation results show the good performance of these resistance estimator and torque response of the drive.

Backpropagation

State variable

10.1109/isda.2009.183

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Citations (4)

Pied kingfisher optimizer: a new bio-inspired algorithm for solving numerical optimization and industrial engineering problems

Neural Computing and Applications (2024)

Anas Bouaouda Fatma A. Hashim Yassine Sayouti Abdelazim G. Hussien

CMA-ES

Bat algorithm

10.1007/s00521-024-09879-5

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Citations (20)

Handling smart-grid with a multi-objective Particle Swarm Optimization algorithm

Mourad Sellam Mohamed Akherraz Yassine Sayouti

In this paper, an improved Multi-objective Particle Swarm Optimization (MOPSO) of a Smart-grid energy flow in order to achieve the lower cost of the consumed energy is presented. The Smart-Grid is provided with different energy sources: fossil energy sources, renewable energy sources (photovoltaic panels, wind turbines...) and consumers' network. The used algorithm is based on the approach of Multi-objective Particle Swarm Optimization algorithms. It is adapted to a generic Smart-Grid model in order to optimize the total cost of the consumers supporting constraints of Smart-Grids and integrating renewable energy sources. The algorithm is simulated on Matlab giving an optimal solution (called Pareto optimal) corresponding to an optimal cost. At the end of this paper, we will analyze the results of the simulation of this algorithm.

10.1109/irsec.2015.7454967

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Citations (1)

Improvement of the induction motor drive's indirect field oriented control performance by substituting its speed and current controllers with fuzzy logic components

Chaymae Fahassa Yassine Sayouti Mohamed Akherraz

The purpose of this paper is to address improvement of the dynamic and load torque rejection of the indirect field oriented control (IFOC), of an induction motor (IM), by replacing all proportional-integral (PI) controllers with intelligent components: fuzzy logic controllers (FLCs). The controllers substituted, are those of the speed and the stator currents of the IFOC. The performance of the proposed fuzzy control structure, of the IM, was studied in different operating conditions, and was compared with the PI control performance in the same conditions. Simulation tests prove the robustness and relevance of the unique structure of fuzzy logic control based IFOC, in different speed ranges with the application of a load.

Robustness

Electronic speed control

10.1109/irsec.2015.7454928

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Citations (7)