Our work

Village Data Analytics brings together high impact technology and our deep energy access market expertise in Africa and Asia.

Our software-enabled service can helps governments and electrification companies to identify viable sites or sales regions, to reduce customer credit risk, to make data-based plans and measure impact.

VIDA is a technology incubated by TFE Energy.

We built the technology with support from the European Space Agency and appliedAI. For more information, visit www.vida.place.

This study, commissioned by the Faraday Institution, explores how battery storage technologies can be viable and competitive in sub-Saharan Africa. In partnership with DNV GL, we explored the potential of battery systems replacing fossil fuel generator use. TFE performed value chain analyses of batteries and generators used in mini-grids and small-scale behind-the-meter power generation. The report also covers a comprehensive techno-economic model and an analysis of batteries and generators at utility scale.

Access to reliable and clean energy is one of the key challenges that inhibit development of the agricultural sector in poor and developing countries. The modernization of manual and fossil-based agricultural practices through clean energy access is a core element for poverty reduction. However, commercial investment is still inaccessible for the majority of the sector and investors struggle to make a profitable case when approaching such high risk opportunities. Investment decision making relies more and more on accurate and data-driven indicators; satellite imagery coupled with analytical tools such as Geographic Information Systems (GIS) are unlocking new ways of extracting high-impact information.

A geospatial model has been developed that considers the Agri-Energy-Water nexus from a value chain perspective, standardises processing methods and offers market-driven outputs which can serve as the first step for identifying and de-risking investment opportunities.

The model is meant to be replicable across countries and agricultural value chains and allows the processing of raw geospatial datasets to obtain the spatial distribution of energy requirements for the electrification of prospective irrigation and crop processing activities.

Furthermore, it offers the ability to extract economic indicators through a techno-economic feasibility assessment to map the areas with the highest potential for electrification. The Nigerian rice value chain has been used to validate the model.

Not all mini-grid connections are equal. A small householder using a minigrid connection to replace dirty and dangerous kerosene will generate a tiny fraction of the revenue of a commercial maize mill operator for example. The latter represents a commercial investment opportunity, the former a socially responsible intervention.
Till now, these very different customers have been lumped together, damaging the financial case for private sector investors and muddying the waters for social impact or national government investment.
For the first time, these connections can be disaggregated and packaged according to the finance most suitable for each. This unbundling promises to open up more targeted developmental interventions and unlock the hitherto inaccessible types of commercial investor necessary for the industry to finally reach scale.

Energy access challenges are not confined to rural off-grid regions, they extend down agricultural value chains to on-grid urban markets where larger processors prepare output that is ready for wholesale or export markets. As one of the first of its kind to explore the agriculture/energy nexus beyond village scale productive uses, this study:

• Describes tools that can be used to evaluate agricultural processes along the entire value chain continuum from small off-grid processors in the village to large on-grid urban factories;

• Combines existing best practice, geospatial data, on-ground surveys and market information to evaluate the energy needs, value addition and practical characteristics of processing steps along three economically significant value chains in Myanmar - rice, cotton and BPO (beans, pulses and oilseeds);

• Outlines opportunities to strategically invest in improving energy access along value chains to increase the value captured by rural farmers, boost processor productivity and strengthen this nationally vital sector.

TFE were contracted by the African Development Bank to implement a Quality Assurance Framework (QAF) for green mini-grids (GMG) in Nigeria. The QAF was originally conceived at a multidisciplinary, high-level stakeholder meeting on mini-grids at the Fourth Clean Energy Ministerial in New Delhi, India, in 2013. The original driver was to “develop standards to set a level playing field, encourage investment, and drive down prices.” As a result of this recommendation, the U.S. Department of Energy (DOE) teamed with the National Renewable Energy Laboratory (NREL) to develop a QAF for isolated GMG power systems. The QAF is a wide-ranging set of standards of power quality, reliability and availability and includes a performance reporting protocol that is based on these standards. This allows the monitoring of GMG performance at both the individual site and portfolio levels.

TFE initially the QAF and performance reporting protocol so that it was applicable to the local context of Nigerian rural GMGs. This was done in close consultation with the Africa Mini-Grid Developers Association (AMDA), NERC, the Rural Electrification Authority (REA) of Nigeria and individual mini-grid developers.

The QAF also includes the reporting of metrics that are required according to the Nigerian Regulator’s Mini-Grid Regulations of 2016. With the use of a web-based platform developed by Odyssey Energy Solutions, the developer can have their own designated dashboard where they will be able to ensure compliance with the regulations and easily monitor the most important performance metrics of their mini-grid operations.

The QAF has now been translated into French for application across West Africa.

In this case study, we demonstrate how earth observation and machine learning can offer energy demand prediction in remote villages. The case study in Kenya integrates and compares Village Data Analytics (VIDA) and e-GUIDE. It shows how energy consumption predictions have reached a significant degree of maturity and can help electrification site selection and village-level analysis by providing a thorough assessment of the potential for rural electrification at the scale of the entire country and with the precision of individual villages.

The results presented here employ machine learning techniques to draw insights from satellite imagery and electricity consumption data from grid-connected customers. They show how these technologies enable scalable data-driven energy access planning for government planners, utilities, and off-grid electrification companies.

This case study shows how VIDA can support government planners and DFIs to prepare data-driven mini-grid tenders. In Togo, VIDA conducted a review of the quality of on-ground survey data collected from 317 potential mini-grid villages. Then, we illustrate how VIDA can complement on-ground survey data with additional information and mini-grid specific data analysis.


During this study, we found that survey parameters have weak correlations, making them unreliable to assess the viability of mini-grid sites. We have added our suggestions on:

1. how VIDA can enhance the quality of survey data with additional data

2. how its algorithm can analyze villages for mini-grid viability and

3. how VIDA can support the mini-grid tendering process reliably, at scale and at speed

VIDA is an artificial intelligence (AI) powered, data-enabled service that utilizes satellite imagery, publicly available geospatial data, on-ground survey data, and energy modeling to identify and extract insights about rural villages and to assess their suitability for off-grid electrification, including mini-grids.

In this work with USAID and Power Africa, we analyzed rural settlements in 14 underserved counties of Kenya. By combining information about settlements, grid availability, anchor customers and road infrastructure, VIDA was able to show detailed insights to help solar home system companies plan expansion, sales and logistics and mini-grid developers identify sites. The VIDA methodology can significantly accelerate strategic
decision-making.​

The goal of the project was to validate VIDA’s site assessment capability by comparing VIDA predictions with the on-ground data of operational mini-grids. The test was performed together with ENGIE PowerCorner on 12 mini-grid sites in Tanzania. Actual site performance was shared only after the VIDA prediction was made, then the two were compared.

During the validation, we found that:

• VIDA’s prediction of the viability of mini-grid sites closely matched the actual performance (mostly within 1 sigma or σ), with the exception of one site (2.2σ).

• VIDA was able to correctly predict high revenue in villages, even where survey data incorrectly suggested lower revenue potential.

• VIDA was able to correctly predict significant differences, even for villages that are located in close geographic proximity.

• As a result of the successful validation, the VIDA team might now assess 30 additional sites that ENGIE Energy Access considers for future development

The use of data and digital solutions has a transformative effect on mini-grid and OGS businesses by reducing the cost of power delivered, by reducing the investment risk and by enabling rapid scaling of solutions. This will be instrumental to actually meet global electrification goals (energy for all).

This study by TFE Energy - based on 12 in-depth case studies, around 50 interviews and over 300 companies screened - is the first comprehensive assessment of how data and digital solutions are deployed in the challenging energy access market.

A number of highly innovative solutions are compared across four categories: digital planning tools, digital operations, digital platforms, and digital payments. The report also looks at the financing ecosystem and makes recommendations to all the stakeholders.

We thank all the participants who contributed to the research.

VIDA is an artificial intelligence (AI) powered, data-enabled service that utilizes satellite imagery, publicly available geospatial data, on-ground survey data, and energy modeling to identify and extract insights about rural villages and to assess their suitability for off-grid electrification, including mini-grids.
In this collaboration between TFE Energy and leading mini-grid developer PowerGen, we deployed VIDA in West Africa to test and validate its predictions during a mini-grid site selection campaign by PowerGen.
With VIDA, we analysed an area of 5,500km2, short-listed promising villages and compared them with the results from the on-site surveys performed by PowerGen.
This report outlines the methodology, the validation process, and its results.

Solar PV is growing rapidly in India. The country has become the third largest market for the technology globally. Driven by cost competitiveness, solar PV is now the preferred choice for new power plants by the federal and most state governments. Access to large amounts of capital is essential for the market to maintain its momentum. Our report shows that the financing ecosystem in India is stepping up to meet the needs of the market.

Very little is currently known about energy usage in households and businesses in rural Myanmar. This report is one of the first attempts to provide insights into electricity consumption, demand behaviors of families and businesses in the central Dry Zone, and current and potential demand scenarios that will inform decision makers in the energy and rural development sectors.

India is the fifth largest car market in the world and has the potential to become one of the top three in the near future – with about 400 million customers in need of mobility solutions by the year 2030. That is one side of the coin. The other side is that the country needs a transportation revolution. The current trajectory of adding ever more cars running on expensive, imported fuel and cluttering already overcrowded cities suffering from infrastructure bottlenecks and intense air pollution is unfeasible. India’s cities will choke. A transportation revolution will have many components – better ‘walkability’, public transpor- tation, railways, roads – and better cars. Many of these ‘better cars’ will likely be electric.

Kenya shows that the global microgrid market is ready for significant private investment. While challenges still remain - especially around the regulatory framework and aggregation of projects - there are now enough businesses with viable business models to provide early stage, strategic or even crowd investors with commercially attractive opportunities.

The medium-term growth potential for the microgrid market in Kenya, as well as in other energy access markets including in Africa, South and South-East Asia, is very high.