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Motivations for users to upgrade smart solar solutions (linked to the fellowship Smart Solar Solutions for ALL (S34ALL))

  • Full or part time
  • Application Deadline
    Monday, February 10, 2020
  • Funded PhD Project (Students Worldwide)
    Funded PhD Project (Students Worldwide)

Project Description

Applications are invited for a PhD studentship jointly funded by BBOXX and UCL Engineering. The studentship is for a full-time doctorate over three and a half years.

The lack of access to modern energy services continues to be the reality for over a billion people worldwide[1] .In Sub-Saharan Africa, 65% of the population (37% in urban and over 80% in rural areas) live off the grid[2] and have to rely on polluting fuels such as candles, kerosene or wood. There is a growing need for research into innovative solutions for making energy accessible to all with a stronger understanding of how end-users consume energy and how those trends will evolve.

This research will build on the innovative work of BBOXX (, a next generation utility unlocking potential through energy access. With headquarters in London and operations in 12 countries including Rwanda, Kenya, Togo, DRC and Pakistan, BBOXX offer pay-as-you-go solar power. At the heart of BBOXX is their pioneering management platform, called Pulse, which continuously collects data and insights. BBOXX are currently needing support to assess consumer behaviour and energy consumption trends, both current and future, to understand how best to meet future demand for energy and related solar power appliances.


a) Assess through a combination of smart quantitative data and household consumer surveys why some users would continue using BBOXX’s smart solar home systems versus those who stop.

- For the consumers who continue to use smart solar systems: how consistently they use the systems, for how long and for what type of appliances. What are the payment patterns of those long-standing consumers?

- Develop customer archetypes and market segmentation according to use of systems

- Develop Artificial Neural Network (ANN) models to assess future energy demand for consumers in Rwanda at household level

-Plot demand curves for energy consumption for users in Rwand

B) Business models linked to BBOXX’s ongoing models

- Compare different business models, upgrades and payment patterns such as subsidy versus non-subsidy models.

- Build on existing models to assess which upgrades are likely to be good upgrades and viable for consumers

C) Incentives and upgrades:

- Understand motivations for upgrades to more electrical appliances and/or future services other than electricity. Would consumers be interested in other offerings such as solar water pumping, cooking, internet etc.?

- Assess the nature of incentives such as bonus, referral schemes and other schemes, which could influence upgrades to more appliances, bigger systems and/or other household services (e.g. internet).

- Explore the relation between payment models and energy consumption trends.

- How does ability to pay at current price link with customer payment patterns and seasonality? Where is the sweet spot in terms of pricing energy to ensure high end-user payment performance.

[1] Sustainable Energy for All (2015). Progress Toward Sustainable Energy 2015. Global Tracking Framework Report. International Bank for Reconstruction and Development/The World Bank Group and the International Energy Agency

[2] International Energy Agency (IEA) (2016). World Energy Outlook 2016. OECD/IEA, Paris: France.

Studentship Description

The overall ambition is that the student would work closely with the BBOXX team and build on a knowledge base of long-standing consumers in Rwanda and potentially comparing and contrasting with consumers in another BBOXX country (Kenya, DRC or Togo).

The studentship work would support future market expansion strategy for smart solar services including cooking, internet and other services to be explored during fieldwork in Rwanda and possibly in Togo. Methods to be employed include a combination of qualitative and quantitative methods, in-depth interviews with relevant stakeholders and household surveys on energy consumption and income and expenditure (mixed methods).

We expect elements of machine learning models to predict energy consumption and upgrades trends combined with qualitative tools such as household interviews and consumer interviews to assess behavioural trends. It is anticipated that the student will spend considerable time in Rwanda and possibly some time in Togo during various stages of the doctorate.

Funding Notes

The scholarship covers UCL home/EU tuition fees and provides a tax free stipend per annum, rising with inflation (£17,280 for 2019/2020 academic year, paid pro rata). Research equipment and part travel expenses for one trip per annum will also be covered under the funding.

[International students – we would consider applications from international students of exceptionally high academic merit if they are able to submit written evidence of confirmed funding from a scholarship, governmental agency or other reputed organisation to cover the difference between UK and overseas fees (circa £60,000).]


Applications are invited from UK and EU members, residing in UK. To be eligible to pay fees at the UK/EU rate, you must normally be a national of an EU country, or the relevant family member of an EU national, and have been ordinarily resident within the European Economic Area (EEA), Switzerland or EU Overseas Territories for the 3 year period before the first day of the first academic year of your programme. Please see the UCL Student fee status page to determine your appropriate tuition fee.

Applicants should send a covering letter and CV to Dr. Priti Parikh at [email protected] The successful applicant will then have to apply online to UCL by submitting the PhD application form which they can do by clicking on the Apply now button at the bottom of this page: Please name Dr. Priti Parikh as the proposed supervisor.

Additionally for international students we would need written evidence of funding already secured for covering the fee difference between UK and overseas fees (Circa £60,000)

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