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Cumulative investments (EUR million) per country for 20 years on PV decentralised options (dark blue for higher total amount of investments). B ¬The pie charts indicate the cumulative share of market size (new potential costumers) for each African region.
Source publication
In this data article, we present datasets from the construction of a composite indicator, the Photovoltaic Decentralised Energy Investment (PV-DEI) index, presented in detail in [1]. This article consists of the comprehensive energy-related data collected in practice from several sources, and from the outputs of the methodology described in [1]. Th...
Contexts in source publication
Context 1
... least favourable). Fig. 1 displays the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and indicators. Fig. 2 shows the PV-DEI index variability under three different perspectives private sector, civil society, and international donors: The baseline scenario is determined by the Principle Component Analysis. Fig. 3 depicts the overall investment costs (NPV), are the total amount of investment in PV decentralised option per country. Fig. 1 shows the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and sub-indicators. Fig. 2 illustrates the sensitivity analysis investigating whether the scores and/or their ...
Context 2
... shows the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and sub-indicators. Fig. 2 illustrates the sensitivity analysis investigating whether the scores and/or their associated inferences are robust with respect to changes in the weighting systems indicative of different stakeholder perspectives [28 , 29] . Fig. 3 depicts the estimated required investment needs for decentralised solar-PV in a country. These represent the total amount of investment in solar-PV decentralised technologies per country (if all the mini-grid investments recommended using the analysis of the PV-DEI Index were undertaken). The overall investment costs are calculated by ...
Context 3
... Assessments In addition to the sensitivity assessments documented here, additional sensitivity assessments were conducted to investigate the impact of data winsorization (Fig. SI.3) on PV-DEI ...
Context 4
... least favourable). Fig. 1 displays the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and indicators. Fig. 2 shows the PV-DEI index variability under three different perspectives private sector, civil society, and international donors: The baseline scenario is determined by the Principle Component Analysis. Fig. 3 depicts the overall investment costs (NPV), are the total amount of investment in PV decentralised option per country. Fig. 1 shows the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and sub-indicators. Fig. 2 illustrates the sensitivity analysis investigating whether the scores and/or their ...
Context 5
... shows the breakdown of the PV-DEI index for Congo as an example of the weight of each dimension and sub-indicators. Fig. 2 illustrates the sensitivity analysis investigating whether the scores and/or their associated inferences are robust with respect to changes in the weighting systems indicative of different stakeholder perspectives [28 , 29] . Fig. 3 depicts the estimated required investment needs for decentralised solar-PV in a country. These represent the total amount of investment in solar-PV decentralised technologies per country (if all the mini-grid investments recommended using the analysis of the PV-DEI Index were undertaken). The overall investment costs are calculated by ...
Citations
... Additionally, greenwashing practices within financial institutions may misrepresent certain products or investments as environmentally friendly despite their adverse impacts (Markandya et al., 2017). Furthermore, financial inclusion efforts may not always reach the most vulnerable populations, who might face socio-economic barriers to benefiting from green growth opportunities (Bender et al., 2021). Importantly, knowledge diffusion approaches can sometimes overlook traditional and indigenous knowledge on sustainable resource management, limiting the effectiveness and scope of interventions aimed at supporting green growth (Valente, 2010). ...
... In another dimension, Widera (2021) assesses the thermal comfort of vernacular dwellings, and Genovese and Zoure (2023) advocate an adaptive approach to locally sustainable buildings. Additionally, Bender et al. (2021) introduce the photovoltaic index as a tool for evaluating investments in decentralized photovoltaic energy, underscoring the complexities involved in these investment decisions. ...
This article examines the associated and interactive effects of financial inclusion measured through financial inclusion index and knowledge diffusion, measured through research and development (R&D), internet usage, and education, on green growth measured by CO2 emissions intensity due to production, in Sub-Saharan Africa. Based on a sample of 36 countries and data spanning the period from 2004 to 2018, the analysis employs POLS, Newey & West, and Driscoll & Kraay estimation methods. The findings reveal that financial inclusion, R&D, and internet usage exacerbate CO2 emissions intensity from production, thereby hindering green growth. Conversely, education plays a positive role by reducing production-related CO2 emissions and promoting sustainable practices. Education improves green growth, yet knowledge production through R&D deteriorates green growth when interacting with financial inclusion. Similarly, internet usage, when it interacts with financial inclusion, harms green growth. These results indicate that financial inclusion, R&D, and internet usage negatively impact green growth by increasing CO2 intensity related to production. The study recommends better alignment to green financial inclusion, sustainable R&D, and digital policies with environmental sustainability objectives while advocating for the promotion of environmental education to support green growth. To maximize sustainable development benefits, Sub-Saharan African countries need to adjust their development strategies by incorporating greener practices into financial inclusion, R&D, and digital technologies.
... Considering the results obtained from [14] and [20] we decided to implement a random forest algorithm (MissForest). In fact, MissForest made fewer assumptions about the shape of each dataset and did not require a specific regression model to be specified for imputation. ...
... The completed data sets were normalised to ensure comparability between indicators originally existing at different scales and ranges, and measured in disparate units. Considering the results provided by [13] and [14] , we selected the rescaling or min-max method of normalisation because this preserved the shape of the data distribution for each indicator and did not disproportionately reward or punish exceptional indicator values in contrast to methodologies using Z-scores. ...
In this article we present datasets used for the construction of a composite indicator, the Social Clean Energy Access (Social CEA) Index, presented in detail in [1]. This article consists of comprehensive social development data related to electricity access, collected from several sources, and processed according to the methodology described in [1]. The new composite index includs 24 indicators capturing the status of the social dimensions related to electricity access for 35 SSA countries. The development of the Social CEA Index was supported by an extensive review of the literature about electricity access and social development which led to the selection of its indicators. The structure was evaluated for its soundness using correlational assessments and principal component analyses. The raw data provided allow stakeholders to focus on specific country indicators and to observe how scores on these indicators contributed to a country overall rank. The Social CEA Index also allows to understand the number of best performing countries (out of a total of 35) for each indicator. This allows different stakeholders to identify which the weakest dimensions are of social development and thus help in addressing priorities for action for funding towards specific electrification projects. The data can be used to assign weights according to stakeholders' specific requirements. Finally, the dataset can be used for the case of Ghana to monitor the Social CEA Index progress over time through a dimension's breakdown approach.
... Decentralised renewable energy systems, such as PV minigrids or stand-alone systems (e.g., Solar Home Systems) can be deployed rapidly and are able to reduce the need for the development of transmission and distribution infrastructures. This is able to generate direct economic and social impact due to the increase of both population and social infrastructures with access to electricity (Moner-Girona, Bender, et al., 2021). Microgrids for instance can provide electricity not only to households but also to activities closely related to economic development, such as agriculture and farming (Kyriakarakos & Papadakis, 2018), and social sectors (e.g., education and healthcare). ...
... Finally, the datasets were normalized to ensure comparability between indicators expressed at different scales and measured in unequal units. Considering the results provided by Bender et al. (2021) and Moner-Girona, Bender, et al. (2021) the rescaling or min-max method of normalisation was chosen because this was able to preserve the shape of the data distribution for each indicator and did not disproportionately reward or punish exceptional indicator values in contrast to methodologies using Z-scores. ...
New financing in clean energy technologies plays a progressively important role in increasing energy access in Sub-Saharan Africa (SSA). This research investigates the salient social dimensions of clean electricity access with the view to identify the most suitable SSA countries for funding and implementing decentralised renewable energy systems and sheds light on the opportunities for improving social conditions through clean electrification. Our multi-dimensional analysis of social considerations culminates in the Social Clean Energy Access (Social CEA) Index. The composite indicator structure was empirically tested and improved in terms of accuracy and robustness for 35 SSA countries. The Social CEA index captures the status of social factors on health, education, economic development, gender equality, and quality of life related to electricity access. The Social CEA Index strength is assessed by exploring the synergies between electricity access and social development and its progress over time is evaluated through a dimension's breakdown approach in Ghana.
... In one study, it formed the basis for introducing a Environmental and energy resolutions methodology to minimise the risks and effects of the resource curse in developing countries (De Medeiros Costa and Dos Santos, 2013). In another study, the index was one of the factors included in a model to measure decentralised renewable energy investments in sub-Saharan Africa (Bender et al., 2021). The index was also used to analyse the role of financial market integration on initial public offerings in different contexts (Marcato et al., 2018). ...
Purpose
Given the urgency to address the climate change crisis, the purpose of this study was to investigate the impact of 12 macro-level antecedents on energy and environmental (E&E) shareholder activism in 12 developed countries. Focus was placed on shareholder-initiated E&E resolutions.
Design/methodology/approach
Panel regressions were used to evaluate the relationships between the macro-level antecedents and two dependent variables, namely, the number of shareholder-initiated E&E resolutions filed and voting support for these resolutions.
Findings
The number of shareholder-initiated E&E resolutions filed increased slightly over the research period (2010–2019) but received very little voting support on average. Most of the 1,116 considered resolutions centred on the adoption or amendment of nuclear and environmental policies. Several resolutions called for improved E&E reporting. A significant relationship was found between the number of shareholder-initiated E&E resolutions filed and the rule of law.
Research limitations/implications
The empirical evidence confirmed limited voting support for shareholder-initiated E&E resolutions and the importance of the rule of law in advancing the E&E social movement.
Practical implications
As the E&E social movement is gaining momentum, listed companies in the considered countries are likely to experience more pressure from shareholder activists.
Social implications
To achieve participatory and inclusive climate governance, shareholder activists should collaborate more closely with other challengers in the E&E social movement, notably policy makers and those promoting the rule of law.
Originality/value
The authors considered macro-level antecedents of E&E shareholder activism that have received scant attention in earlier studies. Social movement theory was used as a novel theoretical lens.
... It is known that the manufacturing companies that service the oil and gas industry account for a major share of the energy consumed in the manufacturing sector. Also, the application of solar energy in the oil and gas sector (especially upstream) is a major way to drive solar energy integration and environmental sustainability (Bender et al., 2021). Nigeria, Ghana, and Côte d'Ivoire are the obvious leaders in terms of actual power generation. ...
... Due to the high dependency of the main livelihoods in Senegal River Basin (SRB) on water (agriculture, livestock, fisheries), around 85% of its population lives close to the river (Bender et al., 2021). The SRB is highly vulnerable to climate variability and changes, due to the great interdependence between climate and socioeconomic activities, and it could be further challenged by the increasing pressures posed by its population dynamics on natural resources, the subsequent changes in land use and the competition among sectors and users. ...
... The SRB is highly vulnerable to climate variability and changes, due to the great interdependence between climate and socioeconomic activities, and it could be further challenged by the increasing pressures posed by its population dynamics on natural resources, the subsequent changes in land use and the competition among sectors and users. There is a high hydropower potential in the basin and even if currently only two plants are being exploited (one under development), the four riparian countries have planned to increase the number of reservoirs, in order to meet the expected growing demands as well as to regulate the high inter-and intra-annual water availability of the basin (Bender et al., 2021). In the middle valley and delta, agriculture, pastoralism, and fishing are the main activities. ...
The ECOWAS region has one of Africa's highest potentials for energy production, including both non-renewable (oil, gas, and uranium) and renewable sources (hydroelectric, solar energy, wind energy). Despite this significant potential, the region deals with a number of issues that affect its energy strategy. A review and analysis of the social, political, and economic factors influencing regional energy policy are provided in this paper, along with an assessment and forecast of energy policy in the ECOWAS. The analysis of regional energy policy then takes into account demand management, clean energy production, regional energy trade, and hydrocarbon exploration and production. The results show that the ECOWAS nations have started their transition to a renewable energy-based economy. These policies have long-term implications on the world's energy system and have the potential to improve the region's energy policy, even if the consequences are not immediately noticeable.
... The creation of model and testing the performance in the dataset will be the last stage. As a result, the dataset will be evaluated with multiple algorithms to see whether the model is the best match for the dataset [19]. The comparison will also display each process's distinct topologies, relative error, standard deviation, training time, and testing time [20]. ...
The use of Linear Regression in predicting enrolment has been shown to be beneficial, although it varies with various datasets and attributes; varying weights of the correlation of the attributes can be discarded if they do not impact the prediction. Data collecting had grown since prior investigations, resulting in a more complicated dataset with many varieties. As a result of the data being created by multiple clerks, cleaning and combining proved tough; nonetheless, the fundamental parameters remain intact. Different algorithms were examined but Linear Regression obtained the highest accuracy with a 12.398 percentage for the absolute error and a root mean squared of 26.936 to create a tangible model to anticipate the enrolment of Region IVA CALABARZON in the Philippines. This demonstrates that it was 2.067 percentage points more than the prior research.
... One of the leading predictive algorithms is Regression [7] ; this algorithm has been used in medical, statistical, environmental predictions, and even enrollment analysis [8] [9]. It has also been proven that the regression algorithm fits multidimensional datasets [10]. In this case, using this method would allow a broader scope with higher accuracy [11]. ...
... One of the leading predictive algorithms is Regression [7] ; this algorithm has been used in medical, statistical, environmental predictions, and even enrollment analysis [8] [9]. It has also been proven that the regression algorithm fits multidimensional datasets [10]. In this case, using this method would allow a broader scope with higher accuracy [11]. ...
By fitting a linear equation to observable values, linear regression determines the relationship between two variables. The Department of Education enrollment data in the Philippines, specifically in the School Division of Batangas, is needed to produce modules. The data collected is from the division office, where data cleaning was applied. Deep Learning, Decision Tree, Random Forest, Gradient Boosted Tree, Support Vector Machine, and Linear Regression were used to perform the prediction, and linear regression performed the best with an absolute value of 14.465 and a relative error of 84.81%.
... Given the complex and multifaceted nature of sustainable energy access, composite indicators can help attract investment in decentralized electricity generation. An example of this is the PV Decentralized Energy Investments (PV-DEI) index, 47,48 which covers the environmental, social, political, and financial aspects with over 50 individual indicators. High scores in the social dimension imply that the impacts of investing in decentralized PV are likely to significantly improve various social outcomes. ...
A potential response to the COVID-19 pandemic in sub-Saharan Africa (SSA) with long-term benefits is to provide electricity for medical equipment in rural health centers and communities. This study identifies a large gap in the electrification of healthcare facilities in SSA, and it shows that decentralized photovoltaic systems can offer a clean, reliable, quick, and cost-effective solution. The cost of providing renewable electricity to each health facility by a stand-alone PV system is analyzed for a given location (incorporating operational costs). The upfront investment cost for providing electricity with PV to >50,000 facilities (mostly primary health posts) currently without electricity is estimated at EUR 484 million. Analysis of the accessibility and population distribution shows that 281 million people could reduce their travel time to healthcare facilities (by an average of 50 min) if all facilities were electrified.
