4 10 944 Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Hafdaoui, Hichem Kouadri Boudjelthia, El Amin Bouchakour, Salim Belhaouas, Nasreddine Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource The performance of a photovoltaic system depends on several parameters such as temperature, clouds, and the season, which makes the study of PV performance from monitoring databases very complex given the size of the information and the complexity of the phenomena involved. This article applies an artificial intelligence (AI) method based on machine learning (ML). For more efficient analysis, the Support Vector Machine (SVM) is used to simplify and optimize the processing of these data for the study of the performance of PV systems. More precisely, we group a multi-class data variable according to the needs of the analysis using SVMs. In this article, we present all the stages of data processing based on the application of artificial intelligence (AI). We present as an example the results obtained in the study of the performance of a 150W monocrystalline photovoltaic (PV) module after one year of monitoring. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1082 10.54966/jreen.v25i2.1082 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1082/1039 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 2 (2022): Volume 25 (Regular); 199 – 210 Journal of Renewable Energies; Vol. 25 No 2 (2022): Volume 25 (Regular); 199 – 210 2716-8247 1112-2242 10.54966/jreen.v25i2 Subject The topic of the resource Photovoltaic (PV) Monitoring Classification Artificial intelligence Maximum power Title A name given to the resource Use an artificial intelligence method (Machine Learning) for analysis of the performance of photovoltaic systems Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Hadjidj, Nadjiha Benbrahim, Meriem Ounnas, Djamel Mouss, Leila Hayet Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This study discusses the design of the Maximum Power Point Tracking (MPPT) technique for photovoltaic (PV) systems employing a modified incremental conductance (IncCond) algorithm to extract maximum power from a PV module. A PV module, a DC-DC converter, and a resistive load constitute the PV system. In the scientific literature, it is well-documented that typical MPPT algorithms have significant drawbacks, such as fluctuations around the MPP and poor tracking during a sudden change in atmospheric conditions. To solve the deficiencies of conventional methodology, a novel modified IncCond method is proposed in this study. The simulation results demonstrate that the updated IncCond algorithm presented allows for less oscillation around the maximum power point (MPP), a rapid dynamic response, and superior performance. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1081 10.54966/jreen.v25i2.1081 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1081/1038 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 2 (2022): Volume 25 (Regular); 187 – 198 Journal of Renewable Energies; Vol. 25 No 2 (2022): Volume 25 (Regular); 187 – 198 2716-8247 1112-2242 10.54966/jreen.v25i2 Subject The topic of the resource Photovoltaic system MPPT Modified incremental conductance Title A name given to the resource Analysis and Design of Modified Incremental Conductance-Based MPPT Algorithm for Photovoltaic System Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Dantse, Yvan Martino Eke, Samuel Kouokam, Endouche Mezoue, Cyrille Nsouandele, Jean – Luc Mouangue, Ruben Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This work helps in the implementation of wind energy projects in the city of Douala. Wind data used (speed and direction) were collected from January 1, 2020, to December 31, 2020, at a height of 10m. The use of wind speed distribution laws allowed us to obtain predictions of the available wind energy on-site at different altitudes. Then, the wind direction is established for the orientation of the wind turbines and the turbulence analysis is done to highlight the exploitable wind periods. The results show that harnessing wind energy is possible on site from 10 AM to 06 PM. The wind potential at 138 m height has an average speed of 8.15 m/s for an overall energy density of 749.78 W/m2 for roughness class 0, and an average speed of 3.7 m/s for an overall energy density of 69.118 W/m2 for roughness class 4. The wind turbines will be installed in front of the north-north-east direction between 15 and 25°. Finally, the energy mapping of the city's wind resources allows us to estimate the total energy available at a reference height. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1080 10.54966/jreen.v25i2.1080 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1080/1037 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 2 (2022): Volume 25 (Regular); 169 – 186 Journal of Renewable Energies; Vol. 25 No 2 (2022): Volume 25 (Regular); 169 – 186 2716-8247 1112-2242 10.54966/jreen.v25i2 Subject The topic of the resource Weibull parameters Wind potential Energy density Energy mapping Turbulence Title A name given to the resource Wind data modeling and energy mapping of the wind potential in the city of Douala (Cameroun) Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Bouzeffour, Fatih Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This work, based on the data obtained from the literature reported by (Varela et al., 2018), aims to use the artificial neural network approach to predict the heat and mass transfer in a dehumidifier system, using lithium chloride as a liquid desiccant. A neural network model was developed in MATLAB environment based on multilayer perceptron that included an input, hidden, and output layer. The network input parameters are air velocity, air temperature, air humidity ratio, liquid desiccant temperature, liquid flow rate, and liquid desiccant concentration. The network output includes two variables which are the heat transfer coefficient (Kh) and mass transfer coefficient (Km). The performance of the ANN model was evaluated using the statistical parameters between the prediction results and experimental values. The performance regression yields R2 and MSE values of 0.9344 and 9.0032, respectively, for the test data set of heat transfer coefficient (Kh). Moreover, for the mass transfer coefficient (Km), the regression parameter R2 and MSE values for the ANN tests were found to be 0.9657 and 2.0414, respectively. In addition, air velocity, air temperature, solution mass flow rate, and solution concentration are the most influential parameters on the heat and mass transfer between the air and liquid desiccant. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1079 10.54966/jreen.v25i2.1079 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1079/1036 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 2 (2022): Volume 25 (Regular); 157 – 167 Journal of Renewable Energies; Vol. 25 No 2 (2022): Volume 25 (Regular); 157 – 167 2716-8247 1112-2242 10.54966/jreen.v25i2 Subject The topic of the resource Artificial neural network Liquid desiccant Heat and mass transfer coefficient Dehumidification Title A name given to the resource Artificial neural network-based modeling for the prediction of heat and mass transfer coefficient of the adiabatic liquid desiccant system Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Saheb-Koussa, Djohra Aries, Nawel Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This work presents the optimization of a wind-solar-diesel system with battery storage for a continuous and reliable production of electrical energy. In this context, detailed mathematical modeling of the present system and its operation algorithm has been presented. The objective function of the system is to minimize its cost of energy (CoE) which estimates the average lifetime cost of power production per kWh. The cost elements comprising the CoE include investment costs, fuel costs, and operation and maintenance costs. The optimization is performed in the HOMER software in addition to three metaheuristic optimization techniques namely the Cuckoo Search algorithm (CS), the BAT algorithm (BA) and the Firefly algorithm (FA). The simulations conducted in this paper are based on meteorological data collected from an installation in Bouzareah. Simulation results show the excellent properties and superiority of the CS optimization method compared to HOMER, BA and FA algorithms and demonstrate the feasibility of the proposed hybrid PV-wind-diesel-battery system in Bouzareah. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1076 10.54966/jreen.v25i1.1076 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1076/1049 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 127 – 151 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 127 – 151 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource Hybrid energy system Optimization COE HOMER Metaheuristics algorithms Title A name given to the resource Cost optimization of a wind-solar-diesel system with battery storage Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Nediguina, Mahamat Kher Mahamat Tahir, Abakar Barka, Mahamat soulouknga, Marcel Hamda Nsouandele, Jean Luc Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource Chad has done the study and development of renewable resources a priority in its energy mix. Wind energy is one of the renewable sources that can help Chad to develop rural areas and preserve the environment. This study presents from data obtained from NASA, the wind characteristics in Amdjarass, and Fada over thirty (30) years. The wind distribution density and energy potential at different heights were evaluated using the Weibull statistical analysis method. The aim of this paper is to evaluate the wind energy potential of two important sites in Chad. The study shows that over the 30 years, the mean annual wind speeds vary randomly between 4.7 m/s and 5.4 m/s over an average period of 2 years. Eight months of good average wind speeds were recorded, ranging from 5.01 m/s to 6.31 m/s at Amdjarass and 4.92 m/s to 5.70 m/s at Fada. The 04 months of low velocities observed are in the range of 3.211 m/s - 4.064 m/s at Amdjarass and 3.504 m/s - 4.516 m/s at Fada. The power density varies between 21.53 W/m2 and 111.89 W/m2 in Amdjarass, while in Fada, it varies from 19.85 W/m2 to 86.92 W/m2. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1075 10.54966/jreen.v25i1.1075 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1075/1048 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 109 – 126 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 109 – 126 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource Wind energy Wind speed Weibull distribution Wind potential Extrapolation Title A name given to the resource Evaluation of the Wind Power Potential in the Northeast of Chad Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Merizgui, Tahar Bouchiba, Oumelkheir Gaoui, Bachir Birane, Mouhoub Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This paper presents a comparison study in different techniques of maximum power point tracking (MPPT), which have been experimented and validated by simulation in the proposed PV system. The main aim of each MPPT technique is to enhance and optimize the output of photovoltaic (PV) array in dynamic weather conditions through an examination algorithm. Nevertheless, an optimized MPPT technique is described in many sides like achievement, software, precision, convergence velocity, and hardware naturalness. The gained experimental results for the MPPT techniques are compared using the Perturbation and Observation (P&O), Incremental Conductance (IncCond), Short Circuit Current (SCC), Open Circuit Voltage (OCV), and Constant Voltage (CV) at weather conditions variations. These methods were analyzed and their performance was estimated through using the Matlab/Simulink under different types of atmospheric conditions. These results show that the IncCond technique gives larger efficiency, at rapidly changing conditions than the other techniques. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1074 10.54966/jreen.v25i1.1074 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1074/1047 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 93 – 107 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 93 – 107 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource MPPT IncCond algorithm P&O algorithm Solar irradiance Title A name given to the resource Experimental Comparative Study to Achieve the Maximum Power Point Tracking of a PV System Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Houichi, Amira Ghodbane, Hassina Soudani, Azeddine Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource The three-dimensional numerical simulation of laminar mixed convection heat transfer with and without porous medium in a cylindrical duct was carried out in this study. The cylinder is divided into three parts. The first and the third parts are adiabatic, while the central part is subjected to a constant heat flux. The effects of Darcy number, porosity, permeability and Nusselt number on heat transfer were considered. This problem is modeled by the Navier-stokes equations in the fluid region and by the Darcy-Brinkman-Forchheimer equation in the porous region, and for the thermal field the energy equation is used. The resolution of these equations was performed by the computational fluid dynamics code Ansys15.2 software using finite volume approach. The obtained results showed an accumulation of the hot fluid with stratification in the upper part of the pipe while the lower region of the pipe remained at practically constant temperature. The effect of the porous matrix is very noticeable on the velocity profile. The insertion of a porous high permeability medium significantly improves heat transfer. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1073 10.54966/jreen.v25i1.1073 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1073/1046 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 71 – 91 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 71 – 91 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource mixed convection heat transfer porous medium CFD laminar flow finite volume method Darcy-Brinkman- Forchheimer Models Nusselt number Richardson number Title A name given to the resource Study of mixed convection in a horizontal cylindrical pipe partially filled with a porous medium saturated with a single fluid Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Hidouri, Nejib Mouftahi, Mawaheb Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource The paper aims to improve biodiesel production from used cooking oils using response surface methodology (RSM). The influence of important factors on biodiesel yield has been investigated by employing a 5-level-3-factor central composite design (CCD). The findings revealed that these factors have considerable impacts on the yield. Besides, fixing temperature value had no detrimental influence on the effectiveness of having adequate mathematical model and obtaining good results. According to the analysis of variance (ANOVA), the molar ratio was found to be the most significant factor. Besides, a second-order models (R2=0.88) were obtained to anticipate the yield as a function of these variables. It is also found that the following ranges of the studied factors can be used to obtain an optimal biodiesel yield: [6.66:1, 8.72:1], [41.62 min, 78.90 min], and [0.91 wt %, 1.79 wt %] for molar ratio, reaction time, and catalyst amount, respectively. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1071 10.54966/jreen.v25i1.1071 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1071/1045 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 55 – 70 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 55 – 70 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource Waste cooking oil Transesterification RSM CCD Biodiesel yield Title A name given to the resource Response surface methodology (RSM) for biodiesel production from waste cooking oil: Study of fatty acid methyl ester (FAME) yield Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Review Articles Journal of Renewable Energies Dataset Data encoded in a defined structure. Examples include lists, tables, and databases. A dataset may be useful for direct machine processing. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Creator An entity primarily responsible for making the resource Aouissi, Zouhair Chabane, Foued Teguia, Mohamed-Salah Bensahal, Djamel Moummi, Noureddine Brima, Abdelhafid Date A point or period of time associated with an event in the lifecycle of the resource 2023-10-04 Description An account of the resource This experimental study and mathematical modelling aim to improve the heat transfer by convection in different cases of transversal baffles inside a duct of a solar air collector. The study enabled us to formulate a mathematical equation of the heat transfer coefficient as a function of pressure drop and the mass flow rates. This mathematical model gave results that are close to the actual results in different inclination angles of the baffles (45°, 90°, 135°, and mixed between 135°and 45°). Through these results, it is found that the best heat transfer coefficient by convection was in the mode where = 90° and in the mixed mode. It was also noticed that the pressure drop in the mixed mode was smaller. With respect to the thermo-hydraulic performance factor (THPF), the case =45° was retained as the best case. Format The file format, physical medium, or dimensions of the resource application/pdf Identifier An unambiguous reference to the resource within a given context https://revue.cder.dz/index.php/rer/article/view/1070 10.54966/jreen.v25i1.1070 Language A language of the resource eng Publisher An entity responsible for making the resource available Renewable Energy Development Center Relation A related resource https://revue.cder.dz/index.php/rer/article/view/1070/1044 Rights Information about rights held in and over the resource Copyright (c) 2022 Journal of Renewable Energies https://creativecommons.org/licenses/by-sa/4.0 Source A related resource from which the described resource is derived Journal of Renewable Energies; Vol. 25 No. 1 (2022): Volume 25 (Regular); 43 – 54 Journal of Renewable Energies; Vol. 25 No 1 (2022): Volume 25 (Regular); 43 – 54 2716-8247 1112-2242 10.54966/jreen.v25i1 Subject The topic of the resource heat transfer coefficient convection baffles pressure drop mass flow rate solar collector Title A name given to the resource Determination of the heat transfer coefficient by convection, according to shape of the baffles (solar air collector) Type The nature or genre of the resource info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion