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Day-ahead seasonal solar radiation prediction,combining VMD and STACK algorithms

Clean Energy 2023年第4期7卷 911-925页

作者： Saida El Bakali ouadi hamid Saad Gheouany ERERA National School of Arts and CraftsMohammed V UniversityRabatMorocco

This article proposes a method for accurately predicting solar irradiance over a 24-hour horizon to forecast photovoltaic energy generation in a positive-energy *** order to make this prediction,the input data are divided into seasons and preprocessed using the variational mode decomposition(seasonal-VMD)*** VMD method is used for extracting high-bandwidth features from the input data,decomposing them into a finite number of smooth modes and focusing on specific frequency ***,the accuracy of signal extraction using the VMD method can be improved by selecting particular parameters judiciously,which impacts the smoothing and frequency concentration of the extracted *** this regard,the salp swarm algorithm(SSA)is employed to identify the optimal VMD parameters that can be used to enhance extraction *** addition,the obtained residual between the observed solar irradiation data and their decomposed modes is treated to enhance the prediction process.A stacking algorithm(STACK)is used to predict the following 24-hour solar irradiance modes and the residual,which are finally summed to reconstruct the desired *** performances of the proposed prediction method are evaluated using two quantitative evaluation indices:the normalized root mean square percentage error(NRMSPE)and normalized mean absolute percentage error(NMAPE).The proposed model is trained on data collected for three years in Rabat(2019–22).The performance of the proposed model is evaluated by predicting the 24-hour solar irradiance for a different *** proposed approach seasonal-VMD-STACK is compared with two other methods in the case of using VMD-based STACK without season partition and STACK method ***,the proposed method has exhibited stability and proven good results with an NRMSPE of 3.87%and an NMAPE of 1.58%for cloudy days during the test *** results demonstrate that residual preprocessing,seasonal input data partition and appropriate selec

关键词： weather forecasting parametric optimization time series data preprocessing machine learning

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Hybrid-integer algorithm for a multi-objective optimal home energy management system

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Clean Energy 2023年第2期7卷 375-388页

作者： Saad Gheouany hamid ouadi Saida El Bakali ERERA National School of Arts and CraftsMohammed V UniversityRabatMorocco

Most of the energy produced in the world is consumed by commercial and residential *** the growth in the global economy and world demographics,this energy demand has become increasingly *** has led to higher unit electricity prices,frequent stresses on the main electricity grid and carbon emissions due to inefficient energy *** paper presents an energy-consumption management system based on time-shifting of loads according to the dynamic day-ahead electricity *** simultaneously reduces the electricity bill and the peaks,while maintaining user comfort in terms of the operating waiting time of *** proposed optimization problem is formulated mathematically in terms of multi-objective integer non-linear programming,which involves constraints and consumer *** optimal scheduling,the management problem is solved using the hybridization of the particle swarm optimization algorithm and the branch-and-bound *** techniques are proposed to manage the trade-off between the conflicting *** first technique is the Pareto-optimal solutions classification using supervised learning *** second technique is called the lexicographic *** simulations were performed based on residential building energy consumption,time-of-use pricing(TOU)and critical peak pricing(CPP).The algorithms were implemented in *** results of the current work show that the proposed approach is effective and can reduce the electricity bill and the peak-to-average ratio(PAR)by 28% and 49.32%,respectively,for the TOU tariff rate,and 48.91% and 47.87% for the CPP tariff rate by taking into account the consumer’s comfort level.

关键词： home energy management system smart building coordination of home appliances metaheuristic algorithm day-ahead scheduling multi-objective binary non-linear constraint problem

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Filtered High Gain Observer for an Electric Vehicle’s Electro-hydraulic Brake: Design and Optimization Using Multivariable Newton-based Extremum Seeking

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Chinese Journal of Electrical Engineering 2023年第4期9卷 73-87页

作者： Jamal El-bakkouri hamid ouadi Fouad Giri Mohamed Khafallah ENSEM Hassan II University of CasablancaCasablanca BP 8118Morocco ENSAM Rabat Mohammed V UniversityRabat BP 6207Morocco Department of Electrical Engineering University of Caen NormandyCaen 14032France

Designing high-gain observers(HGOs)for the state estimation of an electric vehicle’s electrohydraulic brake(EHB)system is *** type of observer is applicable to model nonlinearities and constant feature ***,they are very sensitive to measurement noise,which is unavoidable in *** first novelty of this study is that it compensates for the measurement noise using a filtered high-gain observer(FHGO)to ensure EHB state *** proposed FHGO provides an estimate of the master cylinder pressure,motor current,and rotor speed from measurements of the rotor *** second novelty is the design of an extremum-seeking(ES)optimization loop to adjust the FHGO gains *** performance of the developed FHGO with ES-based online gain optimization was highlighted in the presence of model uncertainties and output measurement noise using a Matlab/Simulink *** superiority of the FHGO(even with a fixed gain)over a standard high gain observer(SHGO)was also demonstrated.

关键词： Electrohydraulic brake filtered HGO measurement noise optimization extremum-seeking Lyapunov theory

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Adaptive neural network observer for proton-exchange membrane fuel cell system

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Clean Energy 2023年第5期7卷 1078-1090页

作者： Abdelaziz El Aoumari hamid ouadi Jamal El-Bakkouri Fouad Giri ERERA National School of Arts and CraftsMohammed V UniversityRabatMorocco LESE Lab ENSEMHassan II UniversityCasablancaMorocco Normandie University UNICAENENSICAENLAC14000 CaenFrance

This paper develops an adaptive neural network(NN)observer for proton-exchange membrane fuel cells(PEMFCs).Indeed,information on the oxygen excess ratio(OER)value is crucial to ensure optimal management of the durability and reliability of the *** OER indicator is computed from the mass of oxygen and nitrogen inside the PEMFC ***,the measurement process of both these masses is difficult and *** solve this problem,the design of a PEMFC state observer is ***,the behaviour of the fuel cell system is highly non-linear and its modelling is *** to this constraint,a multilayer perceptron neural network(MLPNN)-based observer is proposed in this paper to estimate the oxygen and nitrogen *** notable advantage of the suggested MLPNN observer is that it does not require a database to train the ***,the weights of the NN are updated in real time using the output *** addition,the observer parameters,namely the learning rate and the damping factor,are online adapted using the optimization tools of extremum ***,the proposed observer stability analysis is performed using the Lyapunov *** observer performances are validated by simulation under MATLAB®/Simulink®.The supremacy of the proposed adaptive MLPNN observer is highlighted by comparison with a fixed-parameter MLPNN observer and a classical high-gain observer(HGO).The mean rela-tive error value of the excess oxygen rate is considered the performance index,which is equal to 1.01%for an adaptive MLPNN and 3.95%and 9.95%for a fixed MLPNN and HGO,***,a robustness test of the proposed observer with respect to measurement noise is performed.

关键词： fuel cell system(PEMFC) multilayer perceptron neural network(MLPNN)observer optimization extremum seeking(ES) oxygen excess ratio(OER)

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A Comparison between Sabra and Alfa Fibers in Rubber Biocomposites

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Journal of Bionic Engineering 2019年第4期16卷 754-767页

作者： Wafa Ouarhim hamid Essabif Mohammed-ouadi Bensalah Denis Rodrigue Rachid Bouhfid Abou el kacem Qaiss Moroccan Foundation for Advanced Science Innovation and Research(MAScIR)Composites and Nanocomposites Center(CNC)Rabat 10100Morocco Faculty of Science Laboratory of Mechanic and Materials(LMM)Mohammed V-RabatUniversityRabat 10100Morocco National School of Applied Science(ENSA) Ibn Zohr University-AgadirAgrandir 80000Morocco Department of Chemical Engineering and CERMA Universite LavalQuebec G1V0A6Canada

The main objective of this investigation is to valorize a Moroccan crop residue(Sabra fibers,Agave Americana L.)and to compare with Alfa fibers(,Stipa tenacissima L.)as reinforcement in an elastomeric matrix in term of the relaxation properties,mechanical and rheological *** preparation and properties of these two natural fibers embedded in Styrene-Butadiene Rubber(SBR)are presented with and without the addition of Styrene-Ethylene-Butadiene-Styrene grafted with Maleic Anhydride(SEBS-g-MA)as a coupling *** different series(SBR,SBR/Alfa,SBR/Alfa/SEBS,SBR/Sabra and SBR/Sabra/SEBS)were compounded by extrusion and compression *** a result,the addition of the coupling agent in the elastomeric matrix improves the relaxation properties,mechanical and rheological ***,Sabra fibers show the good results compared to Alfa ***,the Zener model was used to determine the rheological time response of the composites.A good agreement between the experimental data and the model was observed(R^2=0.99).

关键词： Sabra fibers Alfa fibers SBR biocomposite relaxation mechanical and rheological properties Zener model

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Production and Characterization of High Density Polyethylene Reinforced by Eucalyptus Capsule Fibers

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Journal of Bionic Engineering 2018年第3期15卷 558-566页

作者： Wafa Ouarhim Mohammed-ouadi Bensalah Denis Rodrigue hamid Essabir Rachid Bouhfid Abou el kacem Qaiss Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Institute of Nanomaterials and Nanotechnology (NANOTECH) Laboratory of Polymer Processing Rabat Morocco Faculty of Science Laboratory of Mechanic and Materials (LMM) Mohammed V-Rabat University Rabat Morocco Department of Chemical Engineering and CERMA Universite Laval Quebec G1V0A6 Canada

In this work, Eucalyptus Capsule Fibers （ECF） are proposed as a new natural fiber reinforcement to produce bio-composites due to their biological origin, specific smell and color. High Density Polyethylene （HDPE） is used as the matrix to compare three reinforcement types, raw ECF, alkali treated ECF, and ECF treated with PE-graft-maleic anhydride （PE-g-MA） as a coupling agent at three concentrations （5 wt.%, 10 wt%, and 15 wt%）. A complete set of characterization is performed including tension, torsion, hardness, Melt Flow Index （MFI）, Attenuated Total Reflection Fourier Transform Infrared Spectroscopy （ATR-FTIR）, Contact Angle （CA）, Scanning Electron Microscopy （SEM）, Thermogravimetric Analysis （TGA） and Dynamic Mechanical Analysis （DMA）. The results show that the best mechanical and rheological improvements are obtained by using the coupling agent with alkali treated fibers.

关键词： eucalyptus capsule fibers polyethylene alkaline treatment coupling agent mechanical properties

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Mechanical and Thermal Properties of Polypropylene Reinforced with Almond Shells Particles： Impact of Chemical Treatments

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Journal of Bionic Engineering 2015年第3期12卷 483-494页

作者： Fatima Zahra El Mechtali hamid Essabir Souad Nekhlaoui Mohammed ouadi Bensalah Mohammad Jawaid Rachid Bouhfid AbouEIkacem Qaiss Laboratory of Mechanic and Materials (LMM) Mohammed V-Rabat University Faculty of Science Rabat Morocco Moroccan Foundation for Advanced Science Innovation and Research (MAScIR) Institute of Nanomaterials and Nanotechnology (NANOTECH) Laboratory of Polymer Processing Rabat Morocco Laboratory of Mechanics in Processes Energy and Environment National School of Applied Sciences Ibn Zohr University Agadir Morocco Department of Biocomposite Technology Institute of Tropical Forestry and Forest Products (INTROP) Universiti Putra Malaysia 43400 UPM Serdang Selangor Malaysia

Polypropylene （PP） matrix composites reinforced with chemically treated Almond Shell （AS） particles with and without compatibilizer （PP-g-MA） was prepared by a twin-screw extrusion at loading of 20 wt.% AS particles. Two types of chemical treatments （alkali treatment with sodium hydroxide and etherification with dodecane bromide） of the particles were carried out to improve the interface adhesion between particles and PP matrix. Results show that chemical modifications of AS particles affect the mechanical and viscoelastic properties of AS/PP composites. The composites reinforced with alkali treated particles and the compatibilized matrix lead to a notable increase in the Young＇s modulus （14%） compared to the composites with untreated AS particles. The ductility of composite was also evaluated by the yield strain, and results show a notable increase （31%） compared to that of composites with untreated particles. The thermal stability increased with the use of etherification （385 ℃）, with gains in the temperature up to 23 ℃ compared to neat PP （362 ℃）. The achieved results show that the AS/PP composites can be used in several applications. A thermoplastic matrix compsite mixed with treated AS particles appears to be a good alternative to obtain environmentally friendly products.

关键词： PP AS chemical treatment composite extrusion injection

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