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Paying As They Go: Payment Patterns Trends of Solar Home System Users

Domain:

environment and energysocioeconomic

Record type:

paper
Creator:
VasPriLic
Host:avatar

Solar Home Systems, propelled by the Pay-As-You-Go model, have been spearheading rural electrification efforts across Sub-Saharan Africa for over a decade. However, due to a lack of data transparency, there has been limited oversight over the real impact of these installations. This study offers an unprecedented look into the reality of PAYGo connections from the users’ perspective. Through an unsupervised deep learning approach, the study synthesises the payment patterns of over 220,000 SHS users, across Rwanda and Kenya, revealing contrasting experiences. Monthly-paying users are at 2 to 5 times higher risk of early default due to their behavioural preference, while differences between age and sex groups underline the need for more differentiated services. Crucially, however, the analysis exposes a persistent share intermittent energy access patterns and late-term defaults, which are currently not accounted for but can – left unaddressed – significantly undermine confidence in a PAYGo led rural electrification agenda.

Visit

figshare.com

Tags

Data mining and knowledge discoverySemi- and unsupervised learningsolar home systems (SHS)PAYGoEnergy AccessDeep Time-Series Clustering

Licenses

CC BY 4.0

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