Kizilcec, Vivien Marie;
(2021)
Examining the customer journey of solar home system users in Rwanda and forecasting their future electricity demand.
Doctoral thesis (Ph.D), UCL (University College London).
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Abstract
Globally, 771 million people lack access to electricity, out of which 75% live in Sub-Saharan Africa (IEA, 2020b). Electricity grid expansion can be costly in rural areas, which often have low population densities. Solar home systems (SHS) have provided people worldwide an alternative option to gain electricity access. A SHS consists of a solar panel, battery and accompanying appliances. This research aims to advance the understanding of the SHS customer journey using a case study of SHS customers in Rwanda. This study developed a framework outlining households’ pre- to post-purchase experiences, which included awareness and purchase, both current and future SHS usage and finally customers’ upgrade, switching and retention preferences. A mixed methods approach was utilised to examine these steps, including structured interviews with the SHS providers’ customers (n=100) and staff (n=19), two focus groups with customers (n=24), as well as a time series analysis and descriptive statistics of database customers (n=63,299). A convolutional neural network (CNN) was created to forecast individual SHS users’ future electricity consumption in the next week, month and three months based on their previous hourly usage. Despite the volatility of SHS usage data, the CNN was able to forecast individual users’ future electricity more accurately than the naïve baseline, which assumes a continuation of previous usage. The time series analysis revealed an evening usage peak for non-television users, whilst customers with a television experienced an additional peak around midday. SHS recommendations prior and post-purchase were common, highlighting the circular nature of the customer journey. The main purchase reason and usage activity were having a clean energy source and phone charging respectively. A better understanding of the SHS customer journey may increase the number of households with electricity access, as companies can better address the purchase barriers and tap into the power of customer recommendations.
| Type: | Thesis (Doctoral) |
|---|---|
| Qualification: | Ph.D |
| Title: | Examining the customer journey of solar home system users in Rwanda and forecasting their future electricity demand |
| Event: | UCL (University College London) |
| Open access status: | An open access version is available from UCL Discovery |
| Language: | English |
| Additional information: | Copyright © The Author 2021. Original content in this thesis is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) Licence (https://creativecommons.org/licenses/by-nc/4.0/). Any third-party copyright material present remains the property of its respective owner(s) and is licensed under its existing terms. Access may initially be restricted at the author’s request. |
| Keywords: | Solar home system, energy access, off-grid energy, customer journey, electricity forecasting, convolutional neural network |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Civil, Environ and Geomatic Eng |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10137819 |
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