What are the impacts of solar energy on access to energy and sustainable development? : Case of West Africa
AMTEFACT TEZEMBONG Xaviera, OUEDRAOGO Poko Yasminat, SILUE Donakan Christian
2024-12-20`
| Keywords: | A B S T R A C T |
|---|---|
-Solar energy -West Africa -Sustainable development -Decentralized electrification -Energy transition |
Access to reliable and affordable energy remains a challenge in West Africa. In 2020, only 52% of the population had access to electricity, with outages reaching 80 hours per month and costs twice the global average. These barriers hinder economic opportunities, social development, and essential services such as health and education. This article explores the potential of solar energy to address these challenges, highlighting decentralized solar technologies and their socio-economic and environmental impacts. The study uses a mixed methodological approach, combining quantitative and qualitative analyses from data from the World Bank, IRENA, and UNDP, as well as field surveys and interviews with experts and local stakeholders. The results aim to provide practical recommendations to strengthen policy frameworks, promote public private partnerships, and develop inclusive financing mechanisms to foster a sustainable energy transition in West Africa |
Table of Contents
3.2.1. First principal component analysis (PCA1)
3.2.2. Second principal component analysis (PCA2)
3.2.3. Selecting the number of dimensions to retain.
3.3.1. Correlation between variables
3.3.2. Correlation circle of variables
3.3.3. Contribution of variables to the formation of axes
3.3.4. Quality of the representation of variables (Cos² parameter)
3.4.1. Representation of individuals in the factorial plane
3.4.2. Contribution of individuals to the formation of axes
3.4.3. Quality of representation of individuals
Lists of figures:
Figure 2. Representation of energy access data.
Figure 3. Representation of annual population growth data.
Figure 4. Representation of annual mean temperature data.
Figure 5. Representation of Co2 emissions data.
Figure 6. Representation of electricity demand data.
Figure 7. Representation of Human Development Index data.
Figure 8. Representation of data from renewable energy installations.
Figure 9. Representation of rural population data.
Figure 10. Representation of population data.
Figure 11. Representation of financial assistance data for energy access
Figure 12. Representation of unemployment rate data.
Figure 13. Première mise en évidence d’un individu atypique.
Figure 14.Deuxième individu atypique mis en évidence.
Figure 15. Decomposition of total inertia..
Figure 16. Correlation circle of variables.
Figure 17. Contributions of variables.
Figure 18.Quality of the representation of variables.
Figure 19.Representation of individuals in the factorial plane.
Figure 20. Contribution of individuals to the formation of axes..
Figure 21. Quality of representation of individuals.
Figure 22.Classification des variables.
Lists of tables:
Table 1. Definition of variables.
1. Introduction
In West Africa, access to reliable and affordable energy remains a major challenge. In 2020, only 52% of the population had access to electricity. This limited coverage is compounded by frequent power outages of up to 80 hours per month and an average cost of electricity twice the global average, estimated at 0.25$/kWh[1]. These difficulties lead to restricted access to health and education services while increasing dependence on fossil fuels and biomass, sources of pollution[2].
Solar energy represents a promising solution to address these challenges. Indeed, West Africa benefits from exceptional sunshine, with an average irradiation of 3 to 7 kWh/m²/day and a solar potential estimated at 10 TW[3]. These conditions offer an abundant and largely underexploited resource that could transform the region’s energy supply. Several technological innovations are helping to harness West Africa’s solar potential. Among them, photovoltaic systems and mini-grids promote decentralized electrification. This approach meets the needs of rural and urban populations, particularly in countries such as Niger[4], Senegal, Nigeria, and Côte d’Ivoire, where off-grid solutions are seeing increasing adoption. In addition, these solutions help reduce greenhouse gas emissions, thereby contributing to the Sustainable Development Goals (SDGs), particularly SDG 7, which aims to ensure access to clean and affordable energy[5].
Numerous studies have explored solutions to energy challenges in West Africa, with a particular focus on renewable technologies. This section reviews the major works related to solar energy and assesses their contributions, limitations, and implications. To understand the challenges and opportunities related to the adoption of solar energy, it is essential to review the major studies and analyses on the topic.
According to Schneider Electric blog, initiatives such as solar microgrids not only provide a clean and affordable source of energy, but also flexibility for communities, allowing them to maintain their daily activities[6]. For example, projects in Guinea and Mali have demonstrated the effectiveness of decentralized solar systems in improving the living conditions of rural populations[7]. In addition, advances in energy storage technologies, such as large-scale batteries, are also underway to support the integration of solar energy into existing grids. Mandelli et al. demonstrated that solar mini-grids are particularly suitable for meeting the needs of remote rural populations, where conventional electricity infrastructure remains inaccessible[8]. Senegal, for example, has started integrating storage systems into some mini-grid projects to overcome challenges related to the intermittency of solar production[8]. This improves the stability of the electricity supply, reducing blackouts and periods of darkness.
Despite its potential, the adoption of solar energy is hampered by several barriers. These include the high initial cost of infrastructure, financing challenges, and the lack of appropriate institutional policies to encourage large-scale implementation. The IEA (International Energy Agency) 2022 report highlights that access to solar energy remains limited in some regions due to the slow adoption of adequate energy policies and the lack of supporting infrastructure[9]. Solar projects, although growing, do not yet cover all needs. For example, in Cape Verde, more than 95% of rural areas are electrified, while in countries such as Sierra Leone, this rate is less than 5%[10].
Financing renewable energy projects, particularly solar, is a key pillar for the energy transition in West Africa. High initial investments and the lack of inclusive financing mechanisms hamper their large-scale adoption. Traditionally, financing relies on bank loans, institutional investments and public funds, which remain inaccessible to small and medium-sized enterprises or rural communities due to perceived risks and lack of collateral. Energy Service Companies (ESCOs) offer an alternative by taking charge of the financing, installation and maintenance of solar systems, often through energy performance contracts. These contracts ensure that consumers only pay for the energy actually used or saved, making them a suitable solution for low-income households and businesses. However, as highlighted by Oji et al. in their analysis, the viability of this model strongly depends on the ability of ESCOs to mobilize initial funds, often limited by high risk perceptions and unstable institutional frameworks[11]. Similarly, the “pay-as-you-go” model has proven effective in improving rural households’ access to solar energy, particularly by allowing for progressive payments that are adapted to the irregular incomes of populations. However, the article by Oji et al. also highlights some limitations, namely that the adoption of these mechanisms remains uneven due to the high cost of the associated technologies, gaps in the digital infrastructure needed to track payments, and the lack of institutional support to reduce the risks perceived by private investors. These challenges, although significant, could be mitigated by public policies promoting financial guarantees, targeted subsidies, and a more regulatory framework[11]. However, the lack of institutional support limits the mobilization of private capital. West African governments have not yet established sufficiently stable regulatory frameworks to reduce the risks perceived by investors, particularly in rural areas where profitability is less assured[9]. Public funding and international aid therefore remain predominant, hampering the emergence of a dynamic of regional self-financing. Small scale projects, such as community microgrids, are also penalized by their low capacity to offer guarantees. To overcome these challenges, it is necessary to strengthen policy frameworks, encourage public-private partnerships, create regional funds for renewable energy and promote inclusive financing mechanisms adapted to local realities[2] [8]. These measures would help boost the adoption of solar technologies and promote a sustainable energy transition, beneficial for rural and semi-urban populations.
Although innovative approaches such as pay-as you-go financing have facilitated access to solar energy in unserved rural areas, the success of these models remains conditioned by national and regional energy policies. In addition, their development is hampered by challenges such as the sustainability of installations and adaptation to local contexts[12] [13]. The IEA (International Energy Agency) report highlights that, despite growing political will, energy infrastructure remains obsolete in most West African countries. The existing electricity grid is often inadequate to integrate renewable energy, limiting the possibility of developing large-scale solar projects. To overcome these obstacles, it is essential to invest in infrastructure modernization and market reform[9].
Solar technologies, in addition to meeting basic energy needs, promote the creation of local jobs in the installation, maintenance and production of equipment[14]. They also contribute to reducing carbon emissions and improving living conditions in rural areas. However, these benefits remain concentrated in countries with stable political frameworks and robust economic incentives[2]. To this end, F. Odoi-Yorke et al. explore policies for energy sustainability, including those to promote the adoption of mini solar grids, such as reducing taxes on renewable energy equipment and introducing smart tariffs, combining economic viability and accessibility for rural communities[15]. G. Mutezo and J. Mulopo, for their part, provided a critique on the management of waste related to solar panels and batteries which remains insufficiently addressed in current policies, while recycling and management of electronic waste are crucial to ensure the sustainability of solar solutions[16].
A literature review shows that there are few studies specifically focusing on the impact of solar energy in improving energy access in West Africa. Several gaps persist in current research and solutions. First, few studies focus on the long-term impact of solar electrification on the social and economic dynamics of rural communities, particularly in terms of sustainable job creation and reduction of inequalities. Second, insufficient integration of solar energy in specific sectors.
In this context, this paper aims to explore the role of solar energy in improving access to energy in West Africa. Unlike existing works that focus much more on challenges faced by the large-scale adoption of renewable energies, particularly solar energy; also, on localized approaches and specific solutions, this study adopts a global perspective. It analyzes the interactions between solar energy, human development and environmental sustainability, while taking into account financial and institutional barriers.
This article aims to answer the question: how can solar energy sustainably improve access to energy in West Africa while meeting the needs of vulnerable populations? To do this, it is essential to analyze the link between access to electricity and the human development index, study the dynamics between population and electricity demand, and quantify environmental impacts. It is also appropriate to study the socio-economic impacts of solar energy. Finally, recommendations will be made to propose concrete dynamics aimed at sustainably improving access to energy. The key questions guiding this reflection are as follows:
· How does solar energy contribute to improving access to electricity, particularly in rural areas of West Africa?
· What is the impact of access to solar electricity on human development, measured by the Human Index (HDI) and the socio-economic conditions of populations?
· To what extent do population growth and urban-rural disparities influence the demand for solar energy in the region?
· What are the effects of solar power generation capacities and international financial flows on greenhouse gas emission reduction sustainability?
· What policies, business models and technological solutions can be implemented to remove barriers to the adoption of solar energy and maximize its impact?
To test the potential effects of solar energy on improving energy access, the following hypotheses were formulated:
Hypothesis 1: Targeted solar energy projects reduce disparities in access to electricity between urban and rural areas.
Hypothesis 2: Access to reliable electricity through solar installations improves health, education, and income indicators, leading to a measurable increase in the HDI.
Hypothesis 3: The production of renewable electricity significantly reduces greenhouse gases.
Hypothesis 4: International financial aid and local investments in solar projects promote a sustainable energy transition and reduce dependency on fossil fuels.
Hypothesis 5: The introduction of new low-cost solar technologies (e.g. long-life batteries) reduces the economic and technical barriers to the expansion of solar energy in West Africa.
This article is structured as follows: first, the methodology and materials used for the analysis will be presented. Then, the results obtained will be presented, accompanied by interpretations and discussions aimed at clearly answering the problem. Finally, recommendations will be formulated for policy makers.
Abbreviations and acronyms:
· kWh/m²/day: kilowatt hour per square meter per day
· $/kWh: dollar per kilowatt hour
· ESCO: Energy Service Companies
· SDG: Sustainable Development Goals • SDG7: Sustainable Development Goal number 7
· HDI: Human Development Index
· CO2: Carbon dioxide
· IEA: International Energy Agency
· PV: Photovoltaic (implicit mention in “photovoltaic systems”)
West Africa, our chosen study area, is the western part of Africa and is composed of both coastal and landlocked countries. These countries include Benin, Burkina Faso, Côte d’Ivoire, Cape Verde, Gambia, Ghana, Guinea, Guinea Bissau, Liberia, Mali, Mauritania, Niger, Sierra Leone, and Togo. This is most clearly seen in the Figure 1 bellow:
2. Materials and methods
2.1. Methodology
This study analyzes nearly a decade of data on energy access in West Africa, focusing on the role of solar energy. While there is a wealth of research on energy access at global and continental scales, this study is limited to the 16 countries of West Africa. Its main objective is to assess the evolution of energy access in this region, identifying the factors influencing the adoption of solar energy, the observed impacts, and the solutions that can be implemented to improve energy access in a sustainable manner.
To do this, we collected country-specific information, including population size, installed solar capacity, energy demand, electrification rate, share of renewables in the energy mix, and changes in CO₂ emissions. We also assessed the effectiveness of renewable energy policies and their impact on the economy, taking into account urbanization rates.
The methodology for studying the role of solar energy in improving access to energy and sustainable development in West Africa is based on a mixed approach, combining quantitative and qualitative analyses. The data used come from the World Bank, IRENA, UNDP; regional reports (Energy policies in West Africa, studies on solar electrification projects), surveys and questionnaires (among rural and urban populations to collect data on their energy needs and the observed impacts of solar projects) and interviews (with NGOs and energy project managers to understand the obstacles and opportunities of solar energy.
The variables are organized according to the following dimensions:
· Socio-economic dimension: access to electricity (in % of the population), rural and urban Development population, Index unemployment rate.
· Energy and environmental dimension: electricity demand, installed renewable electricity production capacity (in MW), and CO₂ emissions (in metric tons).
· Contextual factors: average annual temperature (to assess sunshine and its correlation with solar production), annual population growth (impact on energy demand), and total financial flows for access to energy (assessment of external and local financing).
To obtain a current view of energy realities in West Africa, scientific books and articles published in English were consulted. A total of 16 publications were selected, accessible via searches such as “solar energy in West Africa”, “access to renewable energy” and “energy transition” on Google Scholar. The necessary data were collected from reliable sources such as the “Our World in Data” database.
2.2. Matériel
KoboCollect software was used to obtain some data from the populations. The collected data were transferred to Microsoft Excel software, where they were processed, grouped and organized for optimal use. After that, the same data are analyzed with RStudio software to find the answers to our research questions. The software named QGIS was used to create maps highlighting the main results of the study. Finally, we used Microsoft Word software to write this article.
Based on the availability of data for the variables considered in this study, an unbalanced data panel of 16 countries was constructed. Detailed definitions and units of measurement for all variables are provided in the Table 1 :
2.3. Data analysis method
The method adopted to analyze the data is based on the use of factor analysis, in particular Principal Component Analysis (PCA). This approach is suitable for data sets composed mainly of continuous quantitative variables.
Since the variables are expressed in different units, it is essential to bring them to the same scale by applying a centering and reduction process. This allows the data to be normalized, making standardized PCA particularly appropriate for this analysis.
In practice, this method simplifies the analysis by condensing the information in a table into a small number of new variables. After performing the PCA and reducing the components to a limited set allowing a faithful representation without significant loss of information, a classification of the individuals will be carried out to facilitate interpretation. In this context, the individuals analyzed are the West African countries. Their classification will make it possible to evaluate and interpret the results in order to answer the research questions.
The steps of data analysis are as follows:
· Handling missing data: RStudio’s missMDA package, integrated into the FactoMineR package, was used to handle missing data in factor analyses such as PCA. This package performs an imputation of missing values, ensuring that they do not influence the final results, while taking into account correlations between variables and similarities between individuals in the dataset.
· ACP Execution: PCA was performed using RStudio to identify relationships between variables and individuals. The FactoMineR, FactoShiny and Psych packages were used to automate PCA from the collected data.
· Classification of individuals: A classification of individuals was carried out by grouping them into classes according to their degree of similarity on all variables. This step was carried out using the HCPC function of the FactoShiny package.
Table 1. Definition of variables.
| Variables | Unit of measurement | Definitions |
| Access to electricity (% of population) | % de la population | Percentage of the population with access to electricity in the country. |
| Population | Number of people | Total number of inhabitants living in the country |
| Population living in rural areas | Number of people | Number of people residing in rural areas of the country |
| Human Development Index | Index (from 0 to 1) | A composite measure of human development, taking into account health, education and living standards |
| Electricity demand | TWh | Total electricity demand for the country |
| Installed renewable electricity | MW | Installed capacity of electricity from renewable sources |
| CO2 emissions | kt (kilotons) | Total carbon dioxide (CO₂) emissions produced by the country each year |
| Average annual temperature | °C | Average annual temperature recorded in the country |
| Total financial assistance for access to energy | USD | Total amount of financial aid received to improve access to energy |
| Unemployment rate | % | Percentage of the active population without employment |
| Annual population growth rate | % per year | Annual population growth rate. |
2.4. Data collection method
To collect the necessary data from the populations, we chose to use a questionnaire. This questionnaire aims to collect information directly from individuals, in order to understand their experiences, needs and perceptions regarding access to energy, particularly solar energy. This methodological choice makes it possible to cover a representative sample and to obtain quantitative data that can be used for statistical analysis.
Unlike the interview guide, the questionnaire offers the advantage of being able to be administered to a larger number of respondents, while standardizing the responses to facilitate their processing. In addition, it allows exploring socio-economic aspects, energy consumption habits, as well as the constraints and expectations of populations regarding the adoption of solar solutions.
It is structured as follows: identification of respondents, access to electricity, cost of electricity, suggestions and expectations, etc. The questions asked are as follows:
3. Results and discussions
This section of the study aims at the analysis of the collected data (Table 2).We will present the results of the different analyses, the interpretation of which will lead to answers to the different research questions.
3.1. Visualizing data on maps
The Figure 2, Figure 3,Figure 4, Figure 5, Figure 6, Figure 7, Figure 8, Figure 9, Figure 10, Figure 11 and Figure 12 respectively represent the data maps of energy access, annual population growth, annual average temperature, CO2 emissions, electricity demand, human development index, renewable energy installations, rural population, population, financial assistance for energy access and unemployment rate in West Africa.
By analyzing them we see that:
· Cape Verde has more access to electricity,
· Niger has a very growing population,
· Temperatures are high in all countries except Ghana,
· Nigeria emits more CO2 and has a very high demand for electricity with a larger population,
· Burkina Faso and Togo have a higher human development index and much more PV installation,
· The unemployment rate is higher in Burkina Faso.
3.1. Data analysis
3.2.1. First principal component analysis (PCA1)
From the collected data, we perform a factor analysis, more precisely a principal component analysis (PCA). From this analysis, by highlighting the contribution of each individual to the construction of the different axes, we obtain the graph of individuals on the Figure 13.
We
notice that the Nigerian individual is clearly an outlier compared to
the other individuals, with a very high contribution of about 42.5%. We
are therefore dealing with an atypical individual. The fact that Nigeria
is an outlier is explained by Nigeria being the most populous country
and having the largest economy in West Africa, which can create a
significant gap with other countries in the region. So, let’s remove the
outlier and redo the analysis.
3.2.2. Second principal component analysis (PCA2)
From the collected data, we carry out a factor analysis, more precisely a principal components analysis (PCA). From this analysis, by highlighting the contribution of each individualby constructing the different axes, we obtain the graph of individuals on the Figure 14.
3.2.3. Selecting the number of dimensions to retain.
The inertia of the factor axes indicates, on the one hand, whether the variables are structured and suggests, on the other hand, the appropriate number of principal components to study. From our analysis follows the inertia decomposition on the Figure 15.
Figure 15. Decomposition of total inertia..
The first two axes of the analysis express 76.72% of the total inertia of the dataset. This means that 76.72% of the total variability of the data cloud (or variables) is represented in this plane. This is a high percentage, and the first plane therefore effectively represents the variability contained in a large part of the active dataset. This value is higher than the reference value of 50.09%, so the variability explained by this plane is significant. Therefore, the description of the analysis will be limited to these axes only.
3.3. Study of variables
3.3.1. Correlation between variables
According to the results of the analysis, the correlation matrix of the different variables is presented in the Table 3.
Table 3. Correlation matrix.
| AccElec | Pop | PopRurale | HDI | DemElec | CapRenouv | EmCO2 | TempAnn | AidEnerg | TxChom | CroisPopAnn | |
| AccElec | 1.000 | -0.2574 | -0.275 | 0.3009 | -0.2917 | 0.44059 | -0.2586 | -0.4012 | -0.49174 | 0.4384 | -0.4889 |
| CapRenouv | 0.440 | -0.0915 | -0.1379 | 0.7077 | 0.1605 | 1.0000 | -0.04271 | -0.5809 | 0.00476 | 0.4042 | -0.6050 |
| TxChom | 0.4384 | 0.12368 | 0.01591 | 0.4916 | 0.08115 | 0.40422 | 0.167431 | -0.4776 | -0.38141 | 1.00 | -0.56493 |
| HDI | 0.30092 | 0.10810 | -0.077 | 1.000 | 0.3102 | 0.70771 | 0.206989 | -0.509 | -0.13928 | 0.4916 | -0.75961 |
| Pop | -0.2574 | 1.0000 | 0.9662 | 0.1081 | 0.9212 | -0.09150 | 0.99105 | 0.0637 | 0.58041 | 0.1236 | 0.07707 |
| EmCO2 | -0.2586 | 0.9910 | 0.9276 | 0.2069 | 0.9386 | -0.0427 | 1.0000 | 0.0318 | 0.52740 | 0.1674 | 0.00162 |
| PopRurale | -0.2758 | 0.96621 | 1.0000 | -0.0770 | 0.8681 | -0.1379 | 0.92764 | 0.1585 | 0.6985 | 0.01591 | 0.22807 |
| DemElec | -0.2917 | 0.92122 | 0.8681 | 0.3102 | 1.000 | 0.16059 | 0.93864 | 0.082 | 0.64831 | 0.0811 | -0.01636 |
| TempAnn | -0.4012 | 0.06374 | 0.1585 | -0.5098 | 0.0825 | -0.5809 | 0.03181 | 1.000 | 0.33888 | -0.4776 | 0.5491 |
| CroisPopAnn | -0.4889 | 0.07707 | 0.2280 | -0.7596 | -0.0163 | -0.6050 | 0.00162 | 0.5491 | 0.41933 | -0.5649 | 1.000 |
| AidEnerg | -0.491 | 0.5804 | 0.6985 | -0.1392 | 0.6483 | 0.00476 | 0.52740 | 0.3388 | 1.000 | -0.3814 | 0.41933 |
3.3.2. Correlation circle of variables
The correlation circle (Figure 16) represents the projection of the cloud of variables onto the plane.
Interpretation:
· Axis 1 is highly correlated with variables such as electricity demand, CO₂ emissions, population, financial support for energy access, and rural population. From this observation, we can conclude that Axis 1 reflects the relationship between increasing electricity demand, CO₂ emissions, increasing population, and financial support needed to improve energy access, especially in rural areas. It indicates that regions with high electricity demand have challenges related to environmental impact and require financial support for energy access
· Axis2 can be interpreted as a reflection of social and economic development, as countries with high access to electricity and low unemployment rates, which are generally more developed, are contrasted with those with lower HDI and less advanced renewable electricity generation capacity. From this observation, we can conclude that this axis highlights the disparities between countries in terms of sustainable development and energy transition, where more developed countries often have better energy infrastructure and more advanced transition policies.
3.3.3. Contribution of variables to the formation of axes
We are now interested in the contribution of each variable in the formation of each axis. The latter is represented in the Figure 17.
After careful analysis of theFigure 17, we note that for the formation of axis 1, the variables correlated with it contributed with an approximately equal share, with the exception of the annual temperature variable, which had a relatively low contribution compared to the others.
Regarding the formation of axis 2, all the variables correlated with it contributed actively. This is justified by their relatively high contribution values, all in the same order.
What about the representation of the different variables in the reduced space (plane)?
3.3.4. Quality of the representation of variables (Cos² parameter)
There Figure 18 provides information on the quality of representation of each variable in the reduced space. The parameter (Cos²) is the one that allows this quality of representation to be evaluated.
Variables
whose values (cos²) tend to 1 are better represented in the plane.
Therefore, from our representation, we deduce that variables such as
electricity demand and renewable electricity production capacity are
better represented in the reduced space.
Now it is time to study the different individuals (countries) in the dataset.
3.4. Study of individuals
3.4.1. Representation of individuals in the factorial plane
There Figure 19 presents the representation of different individuals on the factorial level.
Dimension 1 separates individuals such as Burkina Faso, Niger, Senegal, Ivory Coast and Mali (on the right of the graph, characterized by a strongly positive coordinate on the axis) from individuals such as Cape Verde and Mauritania (on the left of the graph, characterized by a strongly negative coordinate on the axis).
Dimension 2 contrasts individuals like Ivory Coast and Ghana (at the top of the graph, characterized by a strongly positive coordinate on the axis) with individuals like Gambia and Niger (at the bottom of the graph, characterized by a strongly negative coordinate on the axis).
From this observation, it can be deduced that the energy needs of West African countries differ according to their economic and social situations. Countries with high energy demand, such as Ghana and Côte d’Ivoire, need large solar projects to meet this demand while reducing CO₂ emissions. Countries with limited access to energy, such as Togo and Guinea, would benefit more from small solar networks adapted to rural areas. Overall, solar energy could improve access to energy, support economic growth, and reduce dependence on fossil fuels throughout the region.
3.4.2. Contribution of individuals to the formation of axes
What is the contribution of each individual to the formation of the two dimensions retained for the analysis? La Figure 20 informs us about this.
There is no evidence of an exaggerated contribution from any country, so there are no outliers. However, the highest contributions come from Niger and Ivory Coast, while countries such as Benin, Togo and Guinea have the lowest contributions.
3.4.3. Quality of representation of individuals
Just as in the study of variables, it is also important to check the quality of the representation of each individual in the reduced space. This is visible through the Figure 21.
The majority of individuals are very well represented in the reduced space, with the exception of Togo and Mali. This reinforces the accuracy of the results obtained from the analysis carried out on the reduced space.
3.5. Classification
Classification consists of grouping individuals with very similar characteristics. In our analysis, this was carried out using RStudio software, which resulted in 3classes as shown in the la Figure 22.
Classification synthesis
Class1: Cape Verde.
Class2: Togo, Guinea, Sierra Leone, Liberia, Gambia, Mauritania and Guinea-Bissau.
Class3: Benin, Niger, Mali, Burkina Faso, Senegal.
Class4: Ghana and Ivory Coast.
Characteristics of each class:
Class1: represents a country with unique characteristics, having a small population and specific energy needs, which can benefit from autonomous energy solutions.
Class2: includes countries with economic challenges and limited energy access, often in rural areas, where decentralized solar mini-grids would be useful to improve energy access.
Class3: Iincludes countries with an intermediate level of development and moderate energy needs, for which medium-sized solar projects and local initiatives would be appropriate.
Class4: Includes countries with economic challenges and limited access to energy, often in rural areas, where decentralized solar mini-grids would be useful in improving energy access.
3.6. Interpretations
From this classification and the main characteristics of each class, it follows that West African countries have varied energy needs that require specific strategies for integrating solar energy.
Countries with high energy demand require large solar projects to support their growth while reducing their CO₂ emissions.
Intermediate and moderate need countries would benefit more from medium sized solar projects combined with local initiatives to improve their access to energy in a sustainable manner. Countries with specific needs require stand-alone solutions tailored to their particular contexts.
Countries with limited access and major economic challenges need decentralized solar mini-grids, which are particularly suitable for expanding energy access in rural areas.
Thus, the diversity of situations requires a personalized approach to maximize the impact of solar energy, taking into account the socio economic and geographical specificities of each group.
4. Recommendations
Faced with the constant increase in demand for electricity in most West African countries and its consequences on the economy, we propose the following solutions:
For countries with high energy demand and advanced development:
· Implement large solar projects (photovoltaic power plants) to meet the growing demand for electricity in a sustainable manner.
· Promote public-private partnerships to attract investment in solar infrastructure.
· Encourage research and development in energy storage to ensure a stable supply, even during periods of low sunlight.
For countries with intermediate development and moderate energy needs:
· Develop medium-sized solar projects in urban and peri-urban areas to meet growing needs infrastructure costs. while limiting
· Promote local solar energy initiatives, such as energy cooperatives, to encourage communities to participate in the energy transition.
· Train the local workforce in solar energy professions to stimulate employment and the local economy in the energy sector.
For countries with specific needs (distinct geographical characteristics):
· Implement autonomous energy solutions such as solar micro-grids or individual solar systems adapted to the population and limited energy needs.
· Strengthen local capacities in renewable energy management to enable autonomy in the operation and maintenance of installations.
· Encourage pilot projects to experiment with innovative solutions adapted to local conditions and geographical constraints.
For countries with limited access and major economic challenges (rural and isolated areas):
· Deploy decentralized solar mini-grids in rural areas to provide energy access in communities far from national grids.
· Support international grants and funding to reduce installation costs for low-income communities.
· Promote the use of solar home systems for basic uses (lighting, phone charging, etc.) and improve the quality of life in the most isolated homes.
Common recommendations:
· Strengthen policies and regulations in favor of solar energy to encourage investment and ensure the sustainability of projects.
· Encourage regional cooperation to share knowledge, skills and best practices in solar energy in the region.
· Educate and raise awareness about the benefits of solar energy to increase social acceptability and encourage widespread adoption.
5. Conclusion
In conclusion, it should be noted that access to energy in West Africa, and more specifically the role of solar energy, is a crucial issue for the sustainable development of the region. Our study shows that energy needs vary considerably depending on the socio-economic profiles of countries, with specific challenges for each group. The high energy demand in some countries calls for large-scale solar projects, while other countries, where access to energy is limited, would benefit from more decentralized solutions, such as solar mini-grids.
Our initial hypothesis that solar energy can significantly improve access to energy in West Africa is confirmed by the results. However, the implementation of these solutions must be adapted to the specificities of each country to ensure optimal impact. In addition, the integration of solar energy contributes to reducing dependence on fossil fuels, thus reducing CO₂ emissions, while promoting economic and social development, particularly in rural areas.
We firmly believe that if the proposed recommendations are taken into account by decision-makers, West Africa will be able to move towards a more sustainable energy future, improving the quality of life of its populations and contributing to the fight against climate change.
6. References
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