Nos publications

31 Octobre 2024

Doubik Yemboate Lare1 , Yawovi Nougblega1,2* , Kodjo Kpode3 , Komi Apéléte Amou2,4

ABSTRACT
This paper presents a computational analysis of the thermoelectric efficiency of hybrid solar chimneys equipped with ventilated photovoltaic (PV) panels with multiple fresh air inlets. The problem addressed is the overheating of the photovoltaic cells, which reduces their electrical efficiency. The influence of multiple air inlets on the electrical and thermal performance of PV/T collectors is the focus of this study. The main objective is to reduce the overheating of the photovoltaic cells and improve their efficiency. This is achieved by using multiple passive ventilation sources instead of placing ventilation systems behind the photovoltaic panels to extract heat and distribute warm air. The implicit finite difference approach is used to discretize the governing heat and mass transfer equations, which are then solved using the Thomas algorithm and the iterative Gauss-Seidel method. The results are obtained by adjusting several important factors, including Raleigh and Reynolds numbers and chimney geometric aspects. The results show that the simultaneous addition of several fresh air openings improves the thermal efficiency by 68% and the electrical efficiency by 5% compared to a chimney with a single vertical duct. The study concludes that this system offers an effective solution for improving the performance of photovoltaic panels, thus contributing to clean energy production.

Keywords: aerovoltaics, numerical study, multiple inlets, fresh air jet, electrical efficiency, thermal efficiency

25 Octobre 2024

Kokou Aménuvéla Toka1*, Yawovi Nougbléga1,2, Yemboate Doubik Laré1, Kodjo Kpodé3

Abstract: The operation of building-integrated photovoltaic (BIPV) systems gives rise to a significant proportion of the solar radiation absorbed by the cells being unable to be converted into electricity. This phenomenon consequently increases the temperature. This temperature increase impacts the cells' electrical efficiency, leading to a reduction in their performance and accelerating their degradation. The combination of phase-change materials with insulating fluid blades, situated behind photovoltaic cells, represents a passive cooling solution that optimizes the performance of hybrid photovoltaic systems when incorporated into facades. The present study assesses a system that incorporates paraffin as a PCM and an argon layer in a PV-PCM-argon layer physical model (PVT/ArPCM), in comparison with a PV-PCM system (PVT/PCM), to enhance the thermoelectric performance of photovoltaic systems mounted on façades while ensuring optimal thermal comfort within buildings. The discrete heat transfer equations were solved using the Thomas algorithm and the iterative Gauss-Seidel method in conjunction with the implicit finite difference method. The findings illustrate that the electrical efficiency experienced only a slight increase, estimated at 0.01%, while there was a notable enhancement in the indoor thermal comfort experienced by occupants, with a 65% improvement observed due to the incorporation of an argon-filled thermal screen. The incorporation of an argon layer led to a minor reduction in temperature of 0.01°C in the photovoltaic cells, resulting in a minimal improvement of 0.014% in electrical power production. The phase-changing material incorporated into PVT/ArPCM demonstrated superior thermal management capabilities in comparison to the same material employed in PVT/PCM.

Keywords: Argon layer, Heat transfer, Numerical study, Phase change materials, Photovoltaic coating.

24 Octobre 2024

Kokou Aménuvéla Toka1,*, Yawovi Nougbléga1,2,* and Komi Apélété Amou1,2

Abstract: The low cooling efficiency of photovoltaic panels integrated into building façades restricts their electrical performance. The innovative approach of a dual-fluid photovoltaic-thermal system (BFPVT), incorporating bi-fluid cooling exchangers, appears to be a promising solution for jointly optimizing the electrical and thermal performance of PVT systems. However, despite the introduction of air heat shields to improve this performance, their limited efficiency makes them less competitive. We present a photovoltaic-thermal (PVT) system with a two-channel heat exchanger. The upper channel contains a stagnant fluid, which acts as a heat shield, while the lower, open channel ensures the continuous circulation or evacuation of heat transfer air. A copper metal plate separates the two channels. We examined the impact of various fluids employed as heat shields, including neon, argon, and xenon, in comparison to air, on the thermal and electrical performance of the collector. We employed numerical modeling of convective and conductive transfers to assess the average thermal efficiency of the BFPVT and the rise in PV temperature in the analyzed configuration. The equations were discretized using the implicit finite difference method and solved using the Thomas and Gauss-Seidel algorithms. The results demonstrated an 18% enhancement in thermal efficiency with the utilization of neon. In contrast, the employment of argon and xenon markedly reduced the mean temperature of photovoltaic cells by 4.82 °C and 4.87 °C, respectively. This led to an increase in their electrical efficiency by 0.33% in comparison to air. Thus, argon is regarded as the optimal choice for optimizing electrical efficiency, taking into account both economic and environmental considerations.

Keywords: numerical study; photovoltaic/thermal panels; bi-fluid collector; mixed convection; thermoelectric performance

23 Octobre 2024

Epiphane Zingbe 1,*, Damgou Mani Kongnine 1,2, Bienvenu M. Agbomahena 3, Pali Kpelou 1,4 and Essowè Mouzou 1

Abstract: Carbon-based electrodes have recently been most widely used in P-MFC due to their desirable properties such as biocompatibility, chemical stability, affordable price, corrosion resistance, and ease of regeneration. In general, carbon-based electrodes, particularly graphite, are produced using a complex process based on petroleum derivatives at very high temperatures. This study aims to produce electrodes from bio-pitch and charcoal powder as an alternative to graphite electrodes. The carbons used to manufacture the electrodes were obtained by the carbonisation of Robinia pseudoacacia and Azadirachta indica wood. These carbons were pulverised, sieved to 50 μm, and used as the raw materials for electrode manufacturing. The binder used was bio-pitch derived from coconut shells as the raw materials. The density and coking value of the bio-pitch revealed its potential as a good alternative to coal-tar pitch for electrode manufacturing. The electrodes were made by mixing 66.50% of each carbon powder and 33.50% of bio-pitch. The resulting mixture was moulded into a cylindrical tube 8 mm in diameter and 80 mm in length. The raw electrodes obtained were subjected to heat treatment at 800 ◦C or 1000 ◦C in an inert medium. The electrical resistivity obtained by the four-point method showed that N1000 has an electrical resistivity at least five times lower than all the electrodes developed and two times higher than that of G. Fourier-transform infrared spectroscopy (FTIR) was used to determine the compositional features of the samples and their surface roughness was characterised by atomic force microscopy (AFM). Charge transfer was determined by electrical impedance spectroscopy (EIS). The FTIR of the electrodes showed that N1000 has a spectrum that is more similar to that of G compared to the others. The EIS showed the high ionic mobility of the ions and therefore that N1000 has a higher charge transfer compared to G and the others. AFM analysis revealed that N1000 had the highest surface roughness in this study.

Keywords: bio-pitch; electrodes; mass loss; density; electrical resistivity; roughness

05 Octobre 2024

K. Jacques Kotoko, Komi Sodoga, Yusuf Shaidu, Nicola Seriani, Sangkha Borah, and Katawoura Beltako*

ABSTRACT: The field of materials science has a strong focus on the study of two-dimensional (2D) materials, with particular emphasis on graphene (GR) and its various allotropes such as graphynes (GYs). In this work, we explored through molecular dynamics simulations at finite temperatures the effects of uniaxial loading on GY structures, which led to new phases that arise at specific temperatures. We identified three new phases in α- and [14, 14, 18]-GYs, which we named C16-GY, C14- GY, and C12-GR. These phases have the remarkable property of remaining stable in a wide range of temperatures (T ≤ 4 and 300 K ≤ T ≤ 600 K). Moreover, we have conducted extensive investigations into the mechanical properties of these newly discovered phases. Through molecular dynamics simulations at finite temperatures, using empirical potential, we have gained valuable insights into how these materials behave under different temperature conditions. Our results reveal that at room temperature (300 K), C16-, C14-GYs exhibit high Young moduli in the x-direction (58.85 and 65.88 N/m) compared to α- and [14, 14, 18]-GYs (46.63 and 43.98 N/m), respectively. Additionally, these new phases exhibit mechanical properties that exceed those of phosphorene, germanene, silicene, and stanene. Importantly, both their mechanical and dynamic stability have been positively confirmed. As a result, these materials are promising candidates for various mechanical applications.

20 Septembre 2024

Abstract: The rapid expansion of the solar industry has underscored the importance of photovoltaic installations in the ongoing transition to sustainable energy. With this growth comes the crucial task of effectively monitoring and controlling the power generated. Photovoltaic systems are particularly vulnerable to defects due to their exposure to challenging environmental conditions, which can lead to reduced power output and an increased risk of fire. Therefore, a thorough analysis of any faults is essential in order to mitigate potential damage to the system. The present study proposes a comprehensive analysis of the behavior of a photovoltaic generator comprising four modules. MATLAB/Simulink software is used to model the generator in healthy operation. Subsequently, a simulation of the generator in faulty conditions is conducted, considering four fault cases: partial shading (PS), open circuit fault (OCF), bypass diode disconnected (PSBD), and twinned fault bypass diode disconnected plus open circuit (PSBDOC). A detailed examination of the simulation results for the faults above reveals that the twinned fault results in a substantial reduction in the output current, as well as an elimination of the open circuit voltage of the photovoltaic generator. This contrasts the behavior observed in a system comprising two modules, wherein the open circuit voltage remains unaltered. This particular fault offers a compelling rationale for the monitoring of photovoltaic installations, to enhance overall productivity while avoiding any potential damage to the system.

Keywords: Faults, Modeling, Photovoltaic generator, Simulation.

18 Septembre 2024

HERVÉ KLINKLIN BADAKA1,*, ALEXANDRU M. MOREGA2

Keywords: Pyrolysis; Wood biomass; Seebeck effect; Finite element method (FEM); Numerical simulation.

This paper experimentally and numerically examines biomass carbonization and using thermoelectric modules to recover heat and generate electricity using the finite element method (FEM). Carbonization, conducted at high temperatures, produces charcoal and gases. The study identifies optimal temperatures for module placement, demonstrating that they can generate up to 6.5 W of electricity. Moreover, integrating the chimney to optimize the carbonization process produced hot air with a maximum gain of 11 °C above the ambient temperature. This approach enhances energy efficiency and reduces costs.

09 Septembre 2024

Isiaka Aremua1,∗ and Laure Gouba2

Abstract
In this paper, we study the exotic Landau problem at the classical level where two conserved quantities are derived. At the quantum level, the corresponding quantum operators of the conserved quantities provide two oscillator representations from which we derive two Boson Fock spaces. Using the normalized coherent states which are the minimum uncertainty states on noncommutative configuration space isomorphic to each of the boson Fock space, we form entangled coherent states which are Bell- like states labeled quasi-Bell states. The effect of non-maximality of a quasi-Bell state based quantum channel is investigated in the context of a teleportation of a qubit.

Keywords: teleportation, qubit, entangled, coherent states, noncommutativity

04 Septembre 2024

Delchere Don-tsa1, Messanh Agbeko Mohou1,2, Kossi Amouzouvi3,4, Malik Maaza5,6 and Katawoura Beltako1,

Abstract
The high computational demand of the Density Functional Theory (DFT) based method for screening new materials properties remains a strong limitation to the development of clean and renewable energy technologies essential to transition to a carbon-neutral environment in the coming decades. Machine Learning comes into play with its innate capacity to handle huge amounts of data and high-dimensional statistical analysis. In this paper, supervised Machine Learning models together with data analysis on existing datasets obtained from a high-throughput calculation using Density Functional Theory are used to predict the Seebeck coefficient, electrical conductivity, and power factor of inorganic compounds. The analysis revealed a strong dependence of the thermoelectric properties on the effective masses, we also proposed a machine learning model for the prediction of highly performing thermoelectric materials which reached an efficiency of 95 percent. The analyzed data and developed model can significantly contribute to innovation by providing a faster and more accurate prediction of thermoelectric properties, thereby, facilitating the discovery of highly efficient thermoelectric materials.

Keywords: thermoelectricity, prediction, machine learning, DFT, data analysis, data sciences

30 Août 2024

Mohamed BARATE1, Eyouléki Tcheyi Gnadi PALANGA2, Ayité Sénah Akoda AJAVON3, Kodjo AGBOSSOU4

Abstract—Power grids must integrate information and communication technologies to become intelligent. This integration will enable power grids to be reliable, resilient, and environmentally friendly. The smart grid would help low-income countries to have a more stable power system to boost their development. However, implementing a smart grid is costly and requires specialized skills. This article aims to outline a low-cost transition from conventional power grids to smart grids in low-income countries. It examines the possibility of telecommunications networks participating in implementing smart grids in these countries, to minimize costs. A combination of quantitative and qualitative methods was used. Using Togo as an example, a conceptual scheme for a low-cost smart grid is proposed, with Togo's telecom operators as the telecoms network support. A transition plan to the smart grid is proposed, based on feedback from developed countries.

Keywords—Smart grid; telecommunications network; low cost; low-income countries

30 Août 2024

Guy M. Toche Tchio P 1 , PJoseph Kenfack P 3 P, Joseph Voufo P 3 P, Yves Abessolo Mindzie P 3 P,P PFrancis-Daniel Menga P 4 P, Sanoussi S. Ouro-Djobo P 1, 2

Abstract – In recent years, fault diagnosis has become a major concern for ensuring the sustainability of photovoltaic systems. This article aims to develop a low-cost data acquisition device based on the Arduino card to collect data using sensors on two photovoltaic modules. Four defects were intentionally created on a photovoltaic panel and analyzed individually based on the evolution of current and voltage parameters over time. The results indicate that in the event of a fault, the current drops suddenly with a slight decrease in voltage. Under normal conditions, the maximum observed current was 3.8 A for an irradiation of 904 W/m2, compared to 2.2 A for 909 W/m2 and 32.78°C in the event of partial shading. This value further decreases to a maximum of 1.8 A for 867 W/m2 in an open circuit. The observation reveals that the partial shading fault with a disconnected bypass diode and open circuit has similar characteristics to the open circuit fault. However, it is important to note that this cannot be generalized as the fault only occurs in a configuration of two PV modules in parallel.

Keywords – PV system, acquisition system, PV health status, faults, Arduino.

28 Août 2024

Komlan S. Gadedjisso-Tossou 1,2,* , Tessa Albaric 3, Adam Habouria 3 , Deru Lian 3, Clémentine Symonds 3, Jean-Michel Benoit 3, Joel Bellessa 3 and Alban Gassenq 3

Abstract: Tetrachlorodiethyl Benzimidazo Carbocyanine (TDBC) layers are very interesting for photonics applications due to their huge oscillator strength, narrow absorption and low-cost fabrication. They are mainly used in strong coupling studies but also for wavelength selective grating fabrication, light concentration, absorption enhancement and so on. However, these intrinsic properties, particularly the refractive index, require further investigation. In this work, we first reviewed the values of the refractive index of TDBC layers reported in the literature. Using fitting with the Drude–Lorentz model, differences are highlighted. We then fabricated pure TDBC layers and measured their properties using ellipsometry and absorption spectroscopy. Finally, we also evaluated the refractive index as a function of the layer bleaching. This work shows that although the precise refractive index evaluation of pure TDBC layers is dependent on the measurement method, their oscillator strength force still remains very high without bleaching.

Keywords: TDBC; bleaching; photonics

28 Août 2024

Kanlou Zandjina Dadjiogou a,b,*, Ayit´e S´enah Akoda Ajavon a,b,c, Yao Bokovi a,b,c

A B S T R A C T
In rural areas lacking an electricity grid, cell phone operators use generators to power their facilities. At the same time, however, the local population is finding it difficult to use the cell phones and other electronic devices for which these operators are deploying their efforts. This situation, due to the problem of access to energy, hinders universal access to telecommunications. The present study aims to solve this problem using microgrid techniques. A microgrid consisting of photovoltaic panels, a genset and storage batteries has been designed to meet the needs of cell phone operators’ sites in Bapure, a rural locality in Togo. The focus is on managing energy flows between the various sources of the microgrid, and between the needs of the cell phone operators’ site and those of the local population. To resolve the lack of solar irradiation data at Bapure, hourly solar irradiation was predicted using the Adaptive Neuro Fuzzy Inference System (ANFIS) algorithm to obtain a realistic result. Optimization studies were then carried out using the Particle Swarm Optimization (PSO) algorithm to determine the optimum system configuration to ensure continuity of service at the operator’s site. The simulation results show that the proposed system has a surplus of energy production at all times, which can be used to supply electricity to the population at a cost equal to 0.0185 USD, with a solar energy utilization rate of 98,95 % and a generator that only needs to operate at 0.15 % throughout the year. The results obtained indicate that a renewable energy system can provide a more efficient solution for electrifying the rural mobile operator’s sites and the local population, and can improve the quality of service for the telecommunications industries.

Keywords: Cost of energy Genset Particle swarm optimization Microgrids Universal service

28 Août 2024

Yawovi M. Amouzouvi 1, Koffi Sagna 2,3, Kossi Tepe 2, Kosi Sesime 1, Kossivi B. R. Afoudji 1, Milohum M. Dzagli 1, 3*, Messanh A. Mohou1, Jérémie T. Zoueu 4

Abstract
Heavy metals are released into the environment due to anthropogenic activities. Cement industries are classified among the main sources of environmental pollutants. This study aims to evaluate the ecological and human health risks of heavy metals in soils and leaves from the CIMTOGO cement factory area in Lomé, Togo. Samples were dried successively in open air and in oven at 105 oC for 24 hours. Samples ground and sieved were used in the analysis using a ZEEnit 700 atomic absorption spectrometer and Ion chromatograph IC 1500 Dionex. The amount of heavy metals in the samples as well as the pollution indices were investigated. High concentration of and Cadmium in the soil, and of chromium and lead in the leaves were found. High potential ecological risk index of 157.26 and 303.73 and the pollution load index of 1.02 and 1.39 were found for the soil and the leaf, respectively confirming the deterioration of the quality of the soil and leaves. The hazard index (0.86) closer to 1 indicates that the cement production activities could have harmful impacts on the health of the surrounding populations and the decision makers have to think about the decontamination of the area.

Keywords
Cement factory, Heavy metal, Pollution indexes, Environmental monitoring, Togo

15 Août 2024

 Abdoul-Razak Ali-Tagba 1,2, Mazabalo Baneto 1,2,* and Dumitru Dorin Lucache 3

Abstract: The design of a high energy performance building requires an assessment of the various design options. Energy simulation offers interesting possibilities for clarifying the architect’s decisions at this level, especially in the initial design phases where the greatest opportunities for optimization lie. The aim of this work is to develop an approach for the evaluation and optimal use of energy simulation in the building design phases. To do this, EnergyPlus building simulation software was used to simulate the energy consumption of the Faculty of Electrical Engineering building at “Gheorghe Asachi” Technical University in Iasi, in order to identify the factors influencing energy consumption in buildings. The results of this study show that an increase in the cooling setpoint temperature from 22 ◦C to 28 ◦C in the roof construction can reduce operating temperatures by 14.2% and 20.0%, respectively. This optimization could significantly reduce the hours of thermal discomfort, in a ratio of 6.0 and 3.25, respectively. Consequently, optimizing parameters linked to design and the heating and cooling systems within the building makes it possible to achieve energy savings and ensure thermal comfort in buildings.

Keywords: energy simulation; building design; influence factors; passive strategies; energy performance

08 Août 2024

Kassé Jean Hugues Angbé 1,* , Yawovi Nougbléga 2,3, Satyanarayana Narra 4 and Vidhi Singh 4

Abstract: Côte d’Ivoire has substantially neglected crop residues from farms in rural areas, so this study aimed to provide strategies for the sustainable conversion of these products to hydrogen. The use of existing data showed that, in the Côte d’Ivoire, there were up to 16,801,306 tons of crop residues from 11 crop types in 2019, from which 1,296,424.84 tons of hydrogen could potentially be derived via theoretical gasification and dark fermentation approaches. As 907,497.39 tons of hydrogen is expected annually, the following estimations were derived. The three hydrogen-project implementation scenarios developed indicate that Ivorian industries could be supplied with 9,026,635 gigajoules of heat, alongside 17,910 cars and 4732 buses in the transport sector. It was estimated that 817,293.95 tons of green ammonia could be supplied to farmers. According to the study, 5,727,992 households could be expected to have access to 1718.40 gigawatts of electricity. Due to these changes in the transport, energy, industry, and agricultural sectors, a reduction of 1,644,722.08 tons of carbon dioxide per year could theoretically be achieved. With these scenarios, around 263,276.87 tons of hydrogen could be exported to other countries. The conversion of crop residues to hydrogen is a promising opportunity with environmental and socio-economic impacts. Therefore, this study requires further extensive research.

Keywords: Côte d’Ivoire; strategy; business; hydrogen; crop residues

04 Août 2024

Isiaka Alani1 , Milohum Mikesokpo Dzagli2,3* , Damgou Mani Kongnine1,3 , Satyanarayana Narra4,5 , Zipporah Asiedu4 .

ABSTRACT
Biomethane and hydrogen are promising elements in the transition towards sustainable energy, due to their capacity to mitigate greenhouse gas emissions. In Ghana, efforts to promote sustainable waste valorization for energy production are underway; however, organic waste conversion into biomethane and hydrogen still needs to be expanded. This study aims to evaluate the potential of producing biomethane and hydrogen from the municipal solid waste in Cape Coast, and their injection into the national gas grid. The upgrading biogas obtained from anaerobic digestion of food/organic wastes was used to generate biomethane. The modified Buswell Equation and data from literature were used to estimate the amount of biomethane and hydrogen. The environmental impact was assessed using the CO2 equivalent emissions. The findings reveal that Cape Coast generated approximately 6,400 tons of food waste in 2021, with a projection to 11,000 tons by 2050. Biomethane and hydrogen quantities were estimated at 3,700,000 m³ and 784,000 kg in 2021, respectively. Their projection reaches to 6,600,000 m³ and 1,400,000 kg by 2050. Converting waste into biomethane and hydrogen is an eco-friendly method of their management and use for renewable energy in Ghana. Strategies can be integrated into Ghana national energy policies to encourage waste-to-energy projects.

KEYWORDS
Biomethane, municipal solid waste, food waste management, green hydrogen, pollutant emissions, renewable energy.

04 Juillet 2024

Guy M. Toche Tchio1,*, Joseph Kenfack3, Joseph Voufo3, Yves Abessolo Mindzie3, Blaise Fouedjou Njoya3 and Sanoussi S. Ouro-Djobo1,2,*

Abstract: The application of machine learning techniques for monitoring and diagnosing faults in photovoltaic (PV) systems has been shown to enhance the reliability of PV power generation. This research introduced a novel machine learning classifier for fault diagnosis in PV systems, utilizing an ensemble algorithm known as extra trees (ETC). The study initially proposed a system with two PV modules and developed a low-cost Arduino-based data logger to gather data from the PV system in free-fault and faulty conditions. Subsequently, the study evaluated six other advanced classifiers for fault diagnosis in PV systems, namely logistic regression (LR), k-nearest neighbor (kNN), support vector machine (SVM), decision tree (DT), AdaBoost, and random forest (RF) models using the collected data from the proposed PV system. The assessment of the various models' performance indicated that the extra trees model exhibits superior classification capabilities for partial shading (PS), open circuit (OCF), partial shading with bypass diode disconnected (PSBD), and combined partial shading with bypass diode disconnected plus open circuit (PSBDOC) faults. The results demonstrated that the new ETC classifier achieves an accuracy of 92%, surpassing the 91%, 87%, 7%, and 59% accuracy of the RF, DT, kNN, and LR classifiers, respectively. This highlights the effectiveness of the extra trees model in enhancing fault detection and classification by distinguishing between open circuits and twin faults. Consequently, these results can be utilized to develop advanced diagnostic tools for photovoltaic systems, thereby improving the reliability of solar technology and accelerating the rate of installation.

Keywords: photovoltaics; diagnosis; extra trees; fault; data acquisition system

19 Juin 2024

Moyème Kabe 1,* , Yao Bokovi 2,* , Kwami Senam Sedzro 3 , Pidéname Takouda 4 and Yendoubé Lare 1

Abstract
Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

Keywords: microgrids; optimization; k-means clustering; mixed integer linear programming; onsset

14 Juin 2024

Kokou Amega a,*, Yacouba Moumouni b, Yendoub´e Lar´e c, Ramchandra Bhandari d, Pidename Takouda e, Saidou Madougou

A B S T R A C T
Most developing countries’ electric power system is stressed by an unprecedented demand growth as well as obstacles that call for urgent actions. Therefore, tackling the present-day power-related challenges and ensure dependable and safe electricity may result in improving living conditions. This research aims to comprehend the primary factors that impede power companies in emerging economies and propose ways of addressing them with a focus on Togolese electricity system as a case study., The methodology utilized to study a complex and dynamic system like electricity sector is an integrated model composed of a survey and review of available literature, an interview with energy experts and the SWOT/PESTLE analysis to perform an in-depth and allencompassing analysis. The study revealed that the electrification poverty was 39.47 % at countrywide level that requires an additional power of 220.95 MW to that of 2021 to achieve 100 % of electricity access by 2030. Moreover, the system’s performance is hindered by a number of internal and external bottlenecks. They include but not limited to limitations in policies and regulations; technical difficulties in the transmission, distribution and off-grid subsystems; insufficient investments; and a lack of incentives and taxes rebates. In light of these findings, a model prioritizing a resilient power system was proposed for transforming the outdated power infrastructure in developing countries laying stress upon energy mix planning, transmission and distribution subsectors innovation and effective regional collaboration.

Keywords: SWOT/PESTLE, Power system, Transformation, Reliability, Resiliency, Togo

10 Juin 2024

1,2,3Apaloo Bara Komla Kpomonè, 1,2,3Palanga Eyouleki Tcheyi Gnadi, 1,2,3Bokovi Yao, 4Kuevidjen Dosseh and 5Nomenyo Komla

1Department of Electrical Engineering, Ecole Polytechnique de Lomé (EPL), University of Lomé, Lomé, Togo
2Department of Electrical Engineering, Engineering Sciences Research Laboratory (LARSI), University of Lomé, Lomé, Togo
3Department of Electrical Engineering, Regional Excellence Center for Electricity Management (CERME) University of Lomé, Lomé, Togo
4Department of Operations Management, Electric Community of Benin (CEB), Lomé, Togo
5Laboratory Light, Nanomaterials and Nanotechnology - L2n CNRS UMR 7076, Troyes University of Technology, Troyes, France

Abstract: The prediction model developed in this article is based on the use of meteorological variables to estimate the consumption of electrical energy at the substations of the Electric Community of Benin. The objective is to predict this consumption in order to adapt production to it. The posts (Lomé Aflao, Légbasito, and Lomé port) are the targets that were used in the study.
The input variables are Relative Humidity (H), Direct Normal Irradiance (I), Precipitation (P), Temperature (T), and wind speed (V). The data collection period extends from 2019 to 2021. Multiple linear regression is used as the algorithm. Mean Absolute Error (MAE), root Mean Square Error (MSE), root mean square error (RMSE), and linear correlation coefficient (R2) were used to evaluate the performance of each model. A statistical characterization of each variable is carried out. It shows a good distribution of temperature, relative humidity, and wind speed values. This is not the case for direct normal irradiance, precipitation, and diffuse radiation...
Keywords: Electricity Consumption, Characterization, Meteorological  Variables, Modeling, Multiple Linear Regression

06 Juin 2024

Kokou Dowou1, Yawovi Nougbléga1,2*, Komi Apélete Amou2,3

Bioclimatic building, which consumes less energy, appears to be the answer both to reduce electricity consumption for air conditioning and lighting and to protect the environment. Nowadays, it is essential to develop construction systems based on locally available building materials in the design of building walls and roofs. This study aims to promote the construction of energy-efficient housing using environmentally friendly local materials and provide thermal comfort for occupants. A comparative study of thermal comfort achieved in buildings designed based on the combination of various local building materials in the wall and lightweight roof envelopes is carried out by numerical investigation. Energy equations written by the nodal method on the walls and roof, discretized by the finite difference method, are solved by the iterative Gauss-Seidel method. The indoor air temperatures of the different building types are simulated and the thermal responses of the envelopes are analyzed. The results presented in terms of thermal comfort in buildings constructed using the proposed local materials show that Typha is a naturally insulating material which offers excellent protection against the heat in hot or cold periods in the building. The introduction of insulation plant fibre reduces significantly to 6°C the temperature
inside the building.

Keywords: Numerical simulation, construction systems, thermal comfort, local building materials

27 Mai 2024

Ratousiri Arnaud Abdel Aziz Valea1,2,*, Seydou Ouedraogo3, Moussa Tissologo4, Nafissatou Bientakwoni So2, Jean Fidèle Nzihou1 and Adekunlé Akim Salami5

Received 22 February 2024; Accepted 22 March 2024
Keywords: Cotton residue, Sample, Methanization, Biogas, Optimization

22 Mars 2024

Ratousiri Arnaud Abdel Aziz Valea1,2,*, Seydou Ouedraogo3, Moussa Tissologo4, Nafissatou Bientakwoni So2, Jean Fidèle Nzihou1 and Adekunlé Akim Salami5

Abstract
For optimum methanization of cotton residues, four (4) samples were made up in vases, with cotton residues as the main component. The first sample consisted of 30g of cotton residue and 270 ml of inoculum, the second of 30g of cotton residue, 270 ml of inoculum and 0.1g of sodium, the third of 15 g of cotton residue, 270 ml of inoculum and 15g of cow dung, and the fourth of 15g of cotton residue, 270 ml of inoculum, 15g of cow dung and 0.1g of sodium. It took 75 days to digest the 30 g of organic matter contained in each sample. The results of this study showed that the sample 4, made up of cotton residue, inoculum, cow dung and sodium, gave the highest biogas volume (1.068 m3), methane volume (0.66 m3) and methane content in the biogas (89%). The best conditions for optimal biogas production from cotton residues are those of a combination of cotton residues, inoculum, cow dung and sodium ash. The results of this study provide knowledge for choosing the optimum conditions for the methanization of organic matter from agricultural waste.

Keywords: Cotton residue, Sample, Methanization, Biogas, Optimization

01 Mars 2024

Kanlou Zandjina Dadjiogou*1,2, Ayité Sénah Akoda Ajavon1,2,3, Yao Bokovi1,2,3

ABSTRACT
Decentralized electricity production solutions based on renewable energies are increasingly used in Africa to promote the social inclusion of the population in rural areas. In these areas not served by the electricity network, there are more and more network infrastructures installed by mobile network operators that are powered by genset. These energy sources only serve to provide electricity to the site elements while the local population lives without electricity. The use of microgrid based on renewable energies, particularly solar energy, on these operator sites can contribute to achieving goals 7 and 9c of the Sustainable Development Goals. Indeed, intelligent management of these microgrids can ensure a continuous supply of electricity to the mobile network operators' sites and the use of excess production to offer electricity to the local population. To achieve this convergence between universal access to telecommunications and energy, based on these microgrids, the use of an optimization algorithm for better planning and operating efficiency of these microgrids is essential. To this end, the Particle Swarm Optimization algorithm was used for optimal power flow management in a multi-source and multi-load system to test the ability of microgrids to achieve this new objective. The obtained results showed that an optimal management of these microgrids guarantees a Loss of Power Supply Probability of 0.18 %, a Levelized Cost of Electricity of US$ 0.0187, and a Maximum Renewable Factor of 98%. Low cost of electricity obtained shows that this solution is a real opportunity for increasing universal access to electricity for low-income populations in rural areas. Similarly, the Maximum Renewable Factor value obtained shows a reduction in the running time of the genset, with the consequence of significantly reducing operating costs and greenhouse gas emissions.

KEYWORDS
Battery, Electricity, Generator, Microgrids, Photovoltaics, PSO, Universal service.

01 Décembre 2023

31 Octobre 2023

Oraléou Sangué Djandja , Adekunlé Akim Salami , Haojun Yuan , Hongwei Lin , Zizhi Huang , Shimin Kang

Abstract
Solvothermal liquefaction of biomass has gained attention to produce liquid biofuel andspecialized chemicals. In this study, eXtreme Gradient Boosting was applied forpredicting the bio-oil yield during solvothermal liquefaction of lignocellulosic biowaste.To establish a precise model for predicting the bio-oil yield, the prediction of the biomassconversion was found to be an intermediate ameliorating variable. The combination ofthe contents of biochemical components (cellulose, hemicellulose and lignin) with theoperating factors (temperature, time, solid loading, solvent polarity and solvent density)provided the best prediction for the biomass conversion (R equals to 99.98% for trainingand 97.67% for test). To predict the yield of bio-oil, introduction of the biomassconversion among inputs improved prediction accuracy (R equals to 100% for trainingand 94.4% for test). The best prediction models developed were interpreted using a gametheory-based feature importance and the partial dependence plotting analysis, whichprovided insights into the biomass conversion pathways and the bio-oil generationmechanism. To assist other researchers in predicting, a graphical user interface wascreated. This tool will save both resources and time that would otherwise be spent onmultiple experimental trials and might not yield useful results.

16 Octobre 2023

Ousmane Nikiema1, Damgou Mani Kongnine1, Seydou Ouedraogo2,*, Emmanuel Nanema3 and Adekunlé Akim Salami1

Abstract
This study focuses on the causes of the general protection triggering of the photovoltaic power plant of the Zagtouli site located in Ouagadougou in Burkina Faso, in West Africa. The objective of this work is to diagnose the causes of the photovoltaic power plant decoupling during the injection of PV electricity on the distribution grid. The methodology consists of collecting and analyzing data from the photovoltaic power plant in order to diagnose the causes of the injection decoupling of photovoltaic electricity. The results of this study show that the causes of decoupling of the Zagtouli solar power plant are mainly related to the voltage variation at the connection point outside the admissible range. However, a frequency fault leads to a voltage fault. It is then necessary to set up an automatic dynamic regulation of the voltage dedicated exclusively to the photovoltaic power plant.

Keywords: Photovoltaic power plant, injection, disruption, decoupling, diagnose

13 Octobre 2023

Abstract— Information and Communication Technologies have massively integrated power grids, now known as smart grids. It is becoming difficult to dimension. The idea behind cosimulation is to be able to preview the behavior of the smart grid's physical and functional architecture before it is implemented. This article analyzes the review of co-simulation platforms for power grids and technology and communications networks used in smart grids, to highlight a method for implementing a co-simulation solution. The PSSE simulator as an electrical simulator and OMNET++ as a communication network simulator are proposed to be integrated with the Mosaïk system. The working environment for the co-simulator realization will be the Python language..

Keywords—co-simulator, electrical network, ICT networks

13 Octobre 2023

Abstract— Electrical energy is an essential factor in the development and evolution of human societies whether in terms of improving living conditions or developing industrial. Service interruptions on the network cause losses not only for the distribution company, but also for the network's major customers, thus hampering the development of the country's economy. Service interruptions on the network cause losses not only for the distribution company, but also for the network's major customers, thus hampering the development of the country's economy. Whenever there is a service interruption on the network, the operations experts search for faults in the affected sections of the network. This causes a great deal of damage to customers at the end of the network lines, and the search method is costly for the distribution company, given the equipment used. In our research studies carried out on the source substation with the heaviest customer load, we propose methods based on the use of artificial intelligence based on neural networks, LSTM, ARIMA and Monte Carlo approaches that are less costly and faster for troubleshooting and more appropriate management of predictive maintenance of substation components.

Keywords— Electrical Energy, neural network, LSTM, ARIMA, Monte Carlo simulation, predictive maintenance.