Nos publications

13 Octobre 2023

Abstract - The complementarity of renewable energy resources required for optimal electrification planning is of scientific and, above all, technical interest, to electrify a given region at any given time. Now, with the aim of achieving one of the UN's Sustainable Development Goals (SDG7) - universal access to electricity at the lowest possible cost - studies were carried out on the issue of optimal electrification planning in Togo. The first step was so, to produce an Atlas of Togo, and the second was to plan its electrification, taking into account the least-cost technological options, while considering environmental integrity, energy reliability and guaranteeing access to electricity in off-grid areas. The working method was thus based on Onsset (Open Source Spatial Electrification Tool) combined with geographic information systems (GIS). Onsset is an open source python-programming tool for optimal electrification planning. This approach takes into account the geographical, infrastructural and socio-economic characteristics of each region of the country. It also enables to identify the various possible optimal combinations of electrification, especially in terms of the choice of the most appropriate technologies, depending on the resources available. The optimized model thus obtained is the one specifically adapted to Togo. Optimal electrification planning (different technologies such as grid extension, installation of isolated systems and/or microgrids...) is thus proposed, taking into account their costs (installation, production and operating costs...). Short-term (03 years or less) and long-term (15 years or more) studies were carried out for several scenarios (04). The results of these studies recommend, for low energy demands: in the case of rural areas (< 40 kWh/year per household) in the short term, stand-alone photovoltaic (PV) systems estimated at around 184 million USD with a production capacity of 20 MW. On the other hand, in semi-urban areas, the approach recommends strengthening urban electrical resilience by extending the grid with a capacity of 13 MW, estimated at 63 million USD. Finally, the long-term approach calls for stand-alone photovoltaic systems (USD 280 million with a production capacity of 62 MW), grid extension systems (USD 964 million with a capacity of 274 MW), hydro mini-grid systems (USD 4 million with a production capacity of 1 MW) and PV-hybrid minigrid systems (USD 1,370 million with a production capacity of 0.72 GW).

Keywords—Onsset, optimal electrification, planning, technologies, GIS systems

13 Octobre 2023

Abstract – Supervision, Control And Data Acquisition (SCADA) systems facilitate the collection of data from different substations and electrical equipment in real time by ensuring the supervision of all organs of the electrical network, its management and operation remotely. SCADA uses a telecommunications infrastructure, information and communication technologies (ICT), and the Internet of Things to ensure its operation. The increased use of digital tools and remote access to the SCADA has made it vulnerable to cyberattacks. However, a successful cyberattack on the SCADA network has the potential to disrupt the activities of the electrical network and this could cause serious consequences such as material, human, financial, etc. The aim of this article is to examine, on the basis of a literature review, the various methods for detecting cyber-attacks in smart grids, in particular the SCADA system. A presentation of the SCADA system and an analysis of the various cyber-attacks that threaten it were presented. A summary of the different Machine Learning methods used by researchers to detect cyber-attacks in the SCADA network was also presented. The K-means clustering method was selected for further research to detect cyber-attacks in the SCADA system, in order to protect the latter from cyber threats. Finally, the conceptual scheme and mathematical formulation of the K-means clustering model were proposed.

Keywords – review, cyber-attacks, detection, methods, smart grids, SCADA.

12 Octobre 2023

Abstract—The regulation and self-sufficiency of electrical energy still remains a challenge in some regions for the residential sector. The aim of this study is to determine a prediction model adapted to each category of consumer, taking into account the parameters that make up the electricity network. With this in mind, this work is based on a set of data collected in West Africa, in Togo and more specifically in the city of Lomé, over a period of 1 year 6 months, on the electricity consumption habits of 10 residential properties with characteristics as diverse as unpredictable and the frequency of appearance of certain uncontrollable events. The data were grouped into 2 groups of 5 houses on the basis of the similarity of the parameters characterizing the data. Group 1 has a high rate of load shedding and a relatively low average total electrical load, while Group 2 has little or no-load shedding. The data were processed in two models, one based on Wavelet decomposition hybridized with artificial neural networks and the other based on Kalman hybridized with neural networks. The results show that the Wavelet-neural network (WANN) model is best suited to Group 1, while the Kalman-neural network (KANN) model is best suited to Group 2.

Keywords— prediction, residential electricity, hybrid models, Wavelet, Kalman

02 Octobre 2023

Yawovi Nougbléga1,2, *, Georges Kibalo Tchamie1, Seydou Ouedraogo3

Abstracts: The present study consisted mainly of making the thermal and dynamic analysis of the fluid flows in mixed convection in the chimney integrated into the building with an upper-covered horizontal hybrid thermal photovoltaic collector on a slab roof. The governing equations discretized by the finite difference method resulted in the systems of tri-diagonal algebraic equations, which were solved by Thomas' algorithm and Gauss Seidel's iterative method. Numerical solutions are presented for various geometrical aspect ratios, Rayleigh, and Reynolds numbers. The results are presented in terms of streamlines, isotherms, velocity, heat transfer intensity, and PV cells’ electrical efficiency versus the governing control parameters in detail.

Keywords: Carbon emissions, rooftop photovoltaics, solar energy, thermal comfort, aero voltaic panel

30 Juillet 2023

Agbassou Guenoupkatia,b,c , Adekunlé Akim Salamia,b,c,* , Yao Bokovia,b,c , Piléki Xavier Koussetoub , Seydou Ouedraogoc,d

Abstract. The Weibull distribution function is essential for planning and designing wind-farm implementation projects and wind-resource assessments. However, the Weibull distribution is limited for those areas with high frequencies of calm winds. One solution is to use the hybrid Weibull distribution. In fact, when the wind speed data present heterogeneous structures, it makes sense to group them into classes that describe the different wind regimes. However, the single use of the Weibull distribution presents fitting errors that should be minimized. In this context, mixture distributions represent an appropriate alternative for modelling wind-speed data. This approach was used to combine the distributions associated with different wind-speed classes by weighting the contribution of each of them. This study proposes an approach based on mixtures of Weibull distributions for modelling wind-speed data in the West Africa region. The study focused on mixture Weibull (WW-BAY) and mixture hybrid Weibull (WWH-BAY) distributions using Bayes' theorem to characterize the wind speed distribution over twelve years of recorded data at the Abuja, Accra, Cotonou, Lome, and Tambacounda sites in West Africa. The parameters of the models were computed using the expectation-maximization (E-M) algorithm. The parameters of the models were estimated using the expectation-maximization (E-M) algorithm. The initial values were provided by the Levenberg-Marquardt algorithm. The results obtained from the proposed models were compared with those from the classical Weibull distribution whose parameters are estimated by some numerical method such as the energy pattern factor, maximum likelihood, and the empirical Justus methods based on statistical criteria. It is found that the WWH-BAY model gives the best prediction of power density at the Cotonou and Lome sites, with relative percentage error values of 0.00351 and 0.01084. The energy pattern factor method presents the lowest errors at the Abuja site with a relative percentage error value of -0.54752, Accra with -0.55774, and WW-BAY performs well for the Tambacounda site with 0.19232. It is recommended that these models are useful for wind energy applications in the West African region.

Keywords: Wind speed, hybrid Weibull distribution; Numerical methods; Mixtures models; Bayes theorem; E-M algorithm; Levenberg-Marquardt algorithm

01 Juin 2023

01 Juin 2023

Essossinam Beguedou 1,* , Satyanarayana Narra 1,2 , Komi Agboka 3, Damgou Mani Kongnine 4 and Ekua Afrakoma Armoo 1

Abstract: The process of making cement clinker uses a lot of energy and produces a lot of pollution. Currently, cement companies use a combination of traditional fossil fuels and alternative fuels (AFFuels) to lower their energy consumption and environmental footprint by improving the pyro-system. In a calciner, AF-Fuels can reach a thermal substitution rate (TSR) of up to 80–100%. However, a kiln burner can only achieve a TSR of 50–60%. High TSR values have been provided by improvements in multi-channel burners, proper AF-Fuel feeding point setups, and various AF pre-combustion methods. Significant modeling of the calciner burner and system has also improved TSRs. However, the cement industry has encountered operational problems such as kiln coating build-up, reduced flame temperatures, higher specific heat consumption, and incomplete combustion. There is growing interest in waste substitution, a promising source of AF-Fuel that needs to be integrated into the current cement plant design to solve the calciner operational problems of the cement industry. This study discusses the latest developments and different experimental and modeling studies performed on the direct burning/co-firing of AF-Fuel in the cement industry as well as the incorporation of gasification in cement manufacturing. Based on this, a technically and environmentally improved solution is proposed. The characteristics of both approaches towards pre-calciner function and optimization are critically assessed. The many in-line cement calciner integration technologies and their various configurations for the long-term problems of cement plants are discussed. This project report also focuses on the necessity of creating appropriate calciner models for forecasting calciner production based on various AF-Fuels and their feeding positions in the calciner.

Keywords: In-line calciner; NOx; co-processing; alternative fuel (AF-Fuel); Chengdu Design Calciner (CDC); feeding point of alternative fuel (FP-AF-Fuel)

27 Mai 2023

Leonce Wehnelt TOKAM, titoleonce@gmail.com
Centre d’Excellence Regional pour la Maıtrise de l’Electricite (CERME), University of Lome, Lome, Togo
 
Sanoussi S. OURO-DJOBO
Centre d’Excellence Regional pour la Maıtrise de l’Electricite (CERME), University of Lome, Lome, Togo | Laboratory on Solar Energy, Department of Physics, Faculty of Science, University of Lome, Lome, Togo

Keywords: Non-Intrusive Load Monitoring (NILM), Interests, Applications, Power Consumption

ABSTRACT
In developing effective energy management mechanisms, new concepts have been developed to provide new approaches. Non-intrusive load monitoring (NILM) is an approach that was originally developed to allow the occupants of a room to identify the contribution of each appliance to the total electricity consumption of the room through a single point measurement device. The aim is to provide customers with information that will enable them to act as ``  `  consum'actors", i.e., people who undertake to change their electricity consumption habits for an objective cause. The progress of artificial intelligence in its various forms (machine learning, big data, internet of things) have greatly contributed to increase the interest of NILM among researchers in different fields. Indeed, some of them are adapting this concept to research areas such as water, transport, health, the environment and agriculture. In this context, applications in these fields have been developed to show the potential and benefits of using this approach. In addition to presenting non-intrusive load monitoring (NILM) in its general framework, this article presents the interests and applications of this approach in various fields.

27 Mai 2023

15 Mai 2023

06 Mai 2023

Leonce W. Tokam 1,* and Sanoussi S. Ouro-Djobo 1,2,*
1 Centre d’Excellence Régional pour laMaitrise de l’Électricité (CERME), University of Lome,
Lome 01 BP 1515, Togo
2 Solar Energy Laboratory, Department of Physics, Faculty of Science, University of Lome, Lome 01 BP 1515, Togo
* Correspondence: wtokam@univ-lome.tg (L.W.T.); sourodjobo@univ-lome.tg (S.S.O.-D.)

Abstract: Without an appropriate monitoring system, the condition/state of electrical appliances/devices in operation in households cannot be fully assessed, resulting in uncontrolled expenses. The purpose of load monitoring techniques is to save electricity consumption. With proper controls, overconsumption of energy can be reduced and unwanted activity that can lead to unnecessary electricity consumption can be eliminated. To achieve this, two approaches are used. The first approach, which says that each device is monitored by means of individual meters or metering devices, is called intrusive load monitoring (ILM) and requires expensive deployment of metering devices for its use. In contrast to the first one, the second approach is non-intrusive load monitoring (NILM), which monitors electricity consumption without the need for any intrusion. In this configuration, the total energy consumed is disaggregated into the individual consumption of each load. With progress/advances in artificial intelligence, this approach is gaining interest with influences in other areas of research. Knowing that these developed techniques aim to encourage the occupants of dwellings to save energy by optimizing their electricity consumption, the paper presents a comparative study of these approaches, in order to highlight the strengths as well as the weaknesses of each of them. It is therefore a means of offering researchers the opportunity to make choices according to the orientations given to the research work.

Keywords: electricity consumption; intrusive load monitoring; non-intrusive load monitoring

06 Mai 2023

Leonce W. Tokam 1,* and Sanoussi S. Ouro-Djobo 1,2,*

Abstract: Without an appropriate monitoring system, the condition/state of electrical appliances/ devices in operation in households cannot be fully assessed, resulting in uncontrolled expenses. The purpose of load monitoring techniques is to save electricity consumption. With proper controls, overconsumption of energy can be reduced and unwanted activity that can lead to unnecessary electricity consumption can be eliminated. To achieve this, two approaches are used. The first approach, which says that each device is monitored by means of individual meters or metering devices, is called intrusive load monitoring (ILM) and requires expensive deployment of metering devices for its use. In contrast to the first one, the second approach is non-intrusive load monitoring (NILM), which monitors electricity consumption without the need for any intrusion. In this configuration, the total energy consumed is disaggregated into the individual consumption of each load. With progress/advances in artificial intelligence, this approach is gaining interest with influences in other areas of research. Knowing that these developed techniques aim to encourage the occupants of dwellings to save energy by optimizing their electricity consumption, the paper presents a comparative study of these approaches, in order to highlight the strengths as well as the weaknesses of each of them. It is therefore a means of offering researchers the opportunity to make choices according to the orientations given to the research work.

Keywords: electricity consumption; intrusive load monitoring; non-intrusive load monitoring

29 Mars 2023

Adekunlé Akim Salami1* – Pierre Akuété Agbessi1 – Seibou Boureima 2 –Ayité S. Akoda Ajavon 1

1 Department of Electrical Engineering, Ecole Nationale Supérieure d’Ingénieurs, Centre d’Excellence Régionale pour la Maîtrise de l’Electricité (CERME), University of Lomé, P.O. Box: 1515 Lomé, TOGO
2 Mines, Industry and Geology school of Niamey, Niger

01 Mars 2023

Oraléou Sangué Djandja a b e, Shimin Kang a, Zizhi Huang a, Junqiao Li a, Jiaqi Feng a, Zaiming Tan a, Adekunlé Akim Salami c, Bachirou Guene Lougou d

a Engineering Research Center of None-food Biomass Efficient Pyrolysis and Utilization Technology of Guangdong Higher Education Institutes, Guangdong Provincial Key Laboratory of Distributed Energy Systems, Dongguan University of Technology, Dongguan, Guangdong, 523808, China
b School of Environmental Science and Engineering, Tianjin University, Tianjin, 300350, China
c Centre D'Excellence Régional pour La Maîtrise de L'Electricité (CERME), Université de Lomé, Lomé, BP 1515, Togo
d School of Energy Science and Engineering, Harbin Institute of Technology, 92 West Dazhi Street, Harbin, 150001, China
e Organization of African Academic Doctors (OAAD), Off Kamiti Road, P. O. Box 25305000100, Nairobi, Kenya

Received 22 September 2022, Revised 19 January 2023, Accepted 14 February 2023, Available online 24 February 2023, Version of Record 1 March 2023.

28 Fevrier 2023

Esso-Wazam Honoré Tchandaoa , Akim Adekunlé Salamia,b* , Koffi Mawugno Kodjoa,b ,Amy Nabilioua,b , Seydou Ouedraogoc

a Centre d'Excellence Régional pour la Maîtrise de l'Electricité (CERME), Université de Lomé, 01 BP 1515 Lomé 01, Togo
b Département de Génie Electrique, École Nationale Supérieure d'Ingénieurs (ENSI), Université de Lomé, 01 BP 1515 Lomé 01, Togo
c Laboratoire de Recherche en Sciences de l’Ingénieur (LARSI), Département de Génie Électrique, Institut Universitaire de Technologie, Université Nazi BONI, 01BP 1091 Bobo-Dioulasso 01, Burkina Faso

18 Décembre 2022

Adekunlé Akim Salami1* – Pierre Akuété Agbessi1 – Seibou Boureima 2 –Ayité S. Akoda Ajavon 1

Abstract: The distribution of wind speed and the optimal assessment of wind energy potential are very important factors when selecting a suitable site for a wind power plant. In wind farm design projects for the supply of electrical energy, designers use the Weibull distribution law to analyse the characteristics and variations of wind speed in order to evaluate the wind potential. In our study we used two approaches, namely, the Multilayer Perceptron (MLP) approach and the Support Vector Machine (SVR) approach to determine a distribution law of wind speeds and to optimally evaluate the wind potential. These two approaches were compared to two well-known numerical methods which are the Justus Empirical Method (EMJ) and the Maximum Likelihood Method (MLM). The results show that the neural network approach produces a better fit of the distribution curve with an Root Mean Square Error (RMSE) of 0.00005016 at Lomé, 0.000040289 at
Cotonou site and a more interesting estimate of the wind potential. After that SVR show a better result too with an RMSE of 0.0095618 at the Lomé site and 0.0053549 at the Cotonou site.

Keywords: Neural Network, Support vector Regression, Multilayer perceptron, Wind energy, Weibull distribution

31 Août 2022

Building a highly accurate model for solar cells and photovoltaic (PV) modules based on experimental data is becoming increasingly important for the simulation, evaluation, control, and optimization of PV systems. Powerful, accurate, and more robust optimization algorithms are needed to solve this problem. In this study, a new optimization approach based on the Levenberg–Marquardt algorithm (ImLM) is proposed to estimate the parameters of PV cells and modules and simulate their electrical behavior under all environmental conditions efficiently and accurately. To avoid the premature convergence of the Levenberg–Marquardt algorithm and the long computation time caused by a bad choice of initial values, we propose a new approach. This is a new reduced form leading to a nonlinear relationship of the series resistance and thus allowing to calculate the optimal initial values of the model parameters. Comparisons with other published methods show that the proposed approach gives not only a more accurate final solution but also a fast convergence speed and a better stability. Furthermore, tests on three PV modules of different technologies (multi-crystalline, thin film, and monocrystalline) reveal that the proposed algorithm performs well at different irradiations and temperatures. These results confirm
that the ImLM approach is a valuable tool and can be an effective and efficient alternative for extracting PV model parameters and simulating PV module behavior under different conditions. [DOI: 10.1115/1.4053624]

Keywords: photovoltaic models, parameter extraction, Levenberg–Marquardt algorithm, new reduced form, statistical analysis

06 Août 2022

Kokou Amega, Yendoubé Laré, Yacouba Moumouni, Ramchandra Bhandari & Saidou Madougou

To cite this article: Kokou Amega, Yendoubé Laré, Yacouba Moumouni, Ramchandra Bhandari & Saidou Madougou (2022): Development of typical meteorological year for massive
renewable energy deployment in Togo, International Journal of Sustainable Energy, DOI: 10.1080/14786451.2022.2109026

To link to this article: https://doi.org/10.1080/14786451.2022.2109026

02 Juin 2022

Kokou Amega · Yendoubé Lare ·
Yacouba Moumouni

Received: 14 July 2020 / Accepted: 2 June 2022
© The Author(s), under exclusive licence to Springer Nature B.V. 2022

01 Mars 2022

PaliKpelou1,2,*,DamgouManiKongnine1,2,RogerAsse1,3 and Essowè Mouzou3

Abstract
Carbonizationisathermochemicalprocessthatgeneratesthermalenergyandcharcoal.Thesystemallowingtorecovertheheatenergyforco-,tri-andmulti-generationiscurrentlymoreinvestigated.Theuseofmulti-generationsystemsisbeneficialfromthestandpointofincreasingtheusageofbiomass,energyefficiencyandreducingtheimpactonforests.Theaimofthisarticlewastodesignacarbonizerfitoutwithathermalinsulationlayeranduseitforthecarbonizationofsomelocalbiomasses,namelywoodchipsandteakwood.Aheatrecoverysystemwasthenincorporatedintothecarbonizertocogeneratehotwaterfromthethermalenergyinducedbythecarbonizationprocess.Theresultsobtainedwiththedesignedcarbonizerwere20%and26%inmassyieldrespectivelyforteckwoodandwoodchips.Thesystemdevelopedthatheatrecoverywasabletogenerate25L/hhotwaterat45◦Cand50◦Cduringthefirstandthelastphasesrespectivelyforwoodchipsandteakwoodcarbonization.Theintroductionofthepreheatingsysteminducedasignificantriseofthewater’stemperature.Thehighestmaximumvalueofthehotwatertemperaturewas62◦Cobtainedduringthecarbonizationofbothstudiedfuels.

Keywords: hotwater;preheating;heatrecovery;carbonization;woodchips

31 Janvier 2022

Oral
eou Sangu
e Djandja a, Adekunl
e Akim Salami b, Zhi-Cong Wang a, Jia Duo c, d, e, **, Lin-Xin Yin a, Pei-Gao Duan a, c, d, e, *

a Shaanxi Key Laboratory of Energy Chemical Process Intensification, School of Chemical Engineering and Technology, Xi'an Jiaotong University, Xi'an, Shaanxi, 710049, PR China
b Centre d'Excellence R
egional pour la Maîtrise de l'Electricit
e (CERME), Universit
e de Lom
e, Lom
e, BP 1515, Togo
c Xinjiang Key Laboratory of Environmental Pollution and Bioremediation, Xinjiang Institute of Ecology and Geography, Chinese Academy of Science, Urumqi, 830011, China
d National Engineering Technology Research Center for Desert-Oasis Ecological Construction, Xinjiang Institute of Ecology and Geography, Chinese Academy of Sciences, 818 South Beijing Road, Urumqi, 830011, Xinjiang, China
e University of Chinese Academy of Sciences, Beijing, 100049, China

16 Septembre 2021

Pali Kpelou1,2,*, Damgou Mani Kongnine1,2, Roger Asse1,3 and Essowè Mouzou3

1 Department of Physics, Laboratoire sur l’Energie Solaire, Université de Lomé, Lomé, 01BP 1515, Togo;
2 Centre d’Excellence Régional pour la Maîtrise de l’Electricité, Université de Lomé, Lomé, 01BP 1515, Togo;
3 Department of Physics, Laboratoire de Physique des Matériaux et des Composants à Semi-conducteurs, Université de Lomé, Lomé, 01BP 1515, Togo