Wind energy of Cameroon by determining Weibull parameters: potential of a environmentally friendly energy

Djiela, Raphael Hermann Tonsie; Kapen, Pascalin Tiam; Tchuen, Ghislain

doi:10.1007/s13762-020-02962-z

Cited by 23 publications

(9 citation statements)

References 32 publications

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“…(17) The net output obtained by the calculations is taken as the median of the possible outcomes and is called P 50 . (18) The risk in the economic sense is evaluated by the uncertainties on this value of the potential (see Section 3.3.11). The uncertainties relate to the following: (i) The wind (on the measurement itself and on each of the extrapolation steps)…”

Section: Methodsmentioning

confidence: 99%

“…International Journal of Energy Research approach of each workflow given in the (Figure 4) is to illustrate the analysis procedure of this study. [18,37,38,[40][41][42][43].…”

Section: Methodsmentioning

confidence: 99%

“…The authors concluded, based on these results and discussions, that the best wind turbines at the Elkharga site can be ranked in decent order as V162, V150, and V110. Although there are a number of studies in the open literature that have discussed the wind potential of certain (regions) areas in Cameroon [1][2][3][4][5][6][7][8][14][15][16][17][18][19], as these studies have shown different results, the determination, modification, proposal, and development of optimal and optimized methods for technoeconomic assessments of wind potential and the cost of energy produced are continuing. However, a technoeconomic analysis combined with the development of wind resource maps, in the occurrence of maps of wind speed, energy produced, and cost of production generated using GIS software (geographic information system) by following an applied geographic approach, is necessary.…”

Section: Introductionmentioning

confidence: 99%

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Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

Koung,

Menga,

Bonoma

et al. 2024

International Journal of Energy Research

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This paper performs a technoeconomic analysis of the wind power potential and evaluates the cost of wind power generation in Evodoula, comparing two methods, the conventional method and the uncertainty method based on a comparative spatiotemporal approach using the geographic information system (GIS) software tool. This study is based on satellite wind data measured at 10 m above ground level (AGL) over a 40-year period (1980-2019), by the meteorological service NASA (National Aeronautics and Space Administration)/Goddard Space Flight Center (GSFC). The main objectives are to obtain an appropriate design for a proven optimal location and to assess the viability of wind power at Evodoula. For this type of study, there is little literature available. The optimization of an onshore wind farm and deployment in the wind energy development interest area (ZIDEE) is carried out to obtain a minimum and parsimonious discounted cost production unitary (CPU) of the electricity produced. The results showed that in Okok, a location with a large energy deficit, an onshore wind farm with an electricity generation capacity of 12.5 MW with 5 NORDEX N100-2.5MW wind turbines would have a total energy production (TEP) of about 64.0254825 TWh and a selling price of electricity that would be 0.0034 CAD$/kWh, which is very low compared to the utility price (about 98% cheaper). The total cost of the wind farm would be about $11 million, with a net present cost of about $218 million. The annual profit generated by the wind farm would be over $6 billion. The return on investment (ROI) of the project is estimated at 2880.882%. The constructed onshore wind farm would avoid CO2 emission at over 11 MtCO2,eq/year as the energy generated is from the atmosphere. The wind farm would realize an average annual cash flow estimated at nearly $30 million after 20 years of operation. These savings would allow the installation of CO2 capture systems in conventional power plants. In addition, the analysis of uncertainties and risks was identified and quantified to estimate the confidence levels of the project development results. The risks have been assessed, and we recommend that the total uncertainty of the project is around 15%. The energy values in P75 and P90 are 10.08% and 19.22%, respectively, lower than the energy value in P50 of 11.60 GWh/An. Finally, the main policy recommendations for an inclusive design process are highlighted. The contribution of this study is to assist policy makers in making appropriate decisions in the development and implementation of energy and environmental policy in Cameroon and in many continental areas.

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Section: Methodsmentioning

confidence: 99%

“…International Journal of Energy Research approach of each workflow given in the (Figure 4) is to illustrate the analysis procedure of this study. [18,37,38,[40][41][42][43].…”

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

Koung,

Menga,

Bonoma

et al. 2024

International Journal of Energy Research

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“…The development of wind farm projects requires appropriate technical, economic and socio-environmental planning and assessment. However, previous research on wind in Cameroon has focused mainly on the comparison of numerical methods for estimating Weibull parameters for the installation of a wind farm in Cameroon [10][11][12], the assessment of the potential of wind energy for the cogeneration of electricity and hydrogen in the Far North of Cameroon [13], technical-economic analysis based on meta-heuristic techniques for the optimal sizing of a standalone photovoltaic/wind hybrid system based on hydrogen batteries for rural electrification in Cameroon [14], study of the design and sensitivity analysis of biomass-based distributed hybrid renewable energy systems for rural electrification with a case study of different photovoltaic/wind/battery integrated options in Babadam, northern Cameroon [15], the design of a checkerboard sizing and layout optimization model for a small onshore wind farm with an estimated capacity of 500 kW in Kribi, Cameroon [16]. To our knowledge, only one study has analyzed the suitability of wind farm sites in Cameroon using a Boolean decision-making approach coupled with GIS (geographic information systems) using various climatic, geographic, economic and environmental criteria such as wind resource, slope, road accessibility, proximity to the power grid and optimal distance to airports.…”

Section: Introductionmentioning

confidence: 99%

Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon

Fotsing Metegam,

Bomeni,

Chara-Dackou

et al. 2024

Preprint

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This article presents the suitability analysis of onshore wind farm sites using an AHP (Hierarchical Analysis Process) multi-criteria decision-making (MCDM) approach based on geographic information system modeling (GIS). This analysis is based on different technical aspects (wind speed, elevation, slope), economic (proximity to the electricity network, proximity to roads) and social (proximity to residential areas, population density). The introduction of the factor “population density” and the constraint “required area” rarely used in previous studies makes it possible to refine the results. The data is classified into several categories in a gradual manner, namely unsuitable (0); less suitable (1); suitable (2); highly suitable (3) and most suitable (4). The results of the study show us that the largest percentage relating to spatial coverage is observed in the “suitable” range with 50.89% and the corresponding TWPP (theoretical wind power potential) is 1377.926 GW; it is followed by “highly suitable” 5.67% and a TWPP of 153.652 GW; then “less suitable” with 1.04% and a TWPP of 28.163GW. No areas were identified in “most suitable” and finally the “unsuitable” range with 42.4%. The results show that the most favorable areas are located in the part of the far north of the country corresponding to the strong wind zone. The sensitivity analysis was carried out based on scenario tests (technical, economic and equal-weight) in order to give greater visibility of choice to the different stakeholders who would like to invest in onshore wind energy in Cameroon. This study is useful in more than one way because the results obtained can help investors, the government and other stakeholders to identify potential areas for the deployment of wind energy systems in Cameroon. Furthermore, a study of hybrid solar-wind systems could improve the efficiency of electricity parks in Cameroon.

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“…There are a number of mathematical models such as the Justus method [Justus et al, 1978], Leesen method [Lysen, 1982], maximum likelihood method [Stevens and Smulders, 1979], energy density method [George, 2014], Rayleigh distribution [Tonsie Djiela et al, 2020], Mabchur empirical method [Zohbi et al, 2014], energy pattern method [Akdağ and Dinler, 2009], energy distribution factor method [Akdağ and Güler, 2015] used to determine solar radiation potential based on the Weibull probability distribution, reviewed and analyzed in [Koholé et al, 2023]. According to the conclusion of the authors, based on a statistical study of each of these methods, it was found that each of the considered approaches provides acceptable accuracy results for predicting the amount of solar radiation.…”

mentioning

confidence: 99%

Review of Models for Estimating and Predicting the Amount of Energy Produced by Solar Energy Systems

Simankov,

Buchatskiy,

Onishchenko

et al. 2023

Russian Journal of Earth Sciences

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Energy production based on renewable sources is a fundamental aspect of society’s sustainable development. The involvement of renewable energy sources in the implementation of modern energy systems can significantly reduce the amount of harmful emissions into the atmosphere and provide greater flexibility of energy infrastructure. The first step in determining the feasibility of involving a particular energy source in the overall energy system of the region is a preliminary assessment of the energy potential to determine the possible percentage of substitution of traditional energy. To solve this problem, it is necessary to use the models of energy supply, which are currently presented in a wide variety. In this regard, this paper proposes to consider various models for estimating the solar energy potential, which can be divided into empirical models and models based on the application of modern intelligent data analysis technologies. Such models are based on many different climatic and geographical indicators, such as: longitude of sunshine, ambient temperature, serial number of the day of the current year, amount of precipitation, average and maximum values of wind speed and so on. The paper analyzed the existing models for estimating the amount of energy, which can be used in the system designed to determine the most optimal configuration of the energy system based on the use of various conversion technologies most relevant to the case under study, and also serve as the basis for creating digital twins designed to model and optimize the operation of the projected energy complex

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Wind energy of Cameroon by determining Weibull parameters: potential of a environmentally friendly energy

Cited by 23 publications

References 32 publications

Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

Technoeconomic Analysis of a Wind Power Generation System and Wind Resource Mapping Using GIS Tools: The Case of Twelve Locations in the Commune of Evodoula, Cameroon

Assessment of the Geographic and Technical Potential for Large-Scale Wind Energy Production Using a GIS-Based MCDM-AHP Multi-criteria Analysis Method and Sensitivity Analysis: Case of Cameroon

Review of Models for Estimating and Predicting the Amount of Energy Produced by Solar Energy Systems

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