Solar home systems for improving electricity access: An off-grid solar perspective towards achieving universal electrification

Nishant Narayan

Research output: ThesisDissertation (TU Delft)

658 Downloads (Pure)


Almost a billion people globally lack access to electricity. For various reasons, grid extension is not an immediately viable solution for the un(der-) electrified communities. As most of these electricity-starved regions lie in tropical latitudes, the use of off-grid solar-based solutions like solar home systems (SHS) is a logical approach. However, state-of-the-art SHS is limited in its power levels and availability. Moreover, sub-optimal system sizing leads to either over-utilization --- and therefore, faster degradation --- of the SHS battery, or under-utilization of the SHS battery, leading to higher system costs. Additionally, off-grid SHS designs suffer from a lack of reliable load profile data needed as the first step for an off-grid photovoltaic (PV) system (e.g., SHS) design. The work undertaken in this dissertation aims to analyze the technological limits and opportunities of using SHS in terms of power level, availability, and battery size, lifetime for achieving universal electrification. Firstly, the three main electrification pathways, viz., grid extension, centralized microgrids, and standalone solar-based solutions like pico-solar and SHS are analyzed for their relative merits and demerits. Then, a methodology is presented to quantify the electricity demand of the households in the form of load profiles for the various tiers of electricity access as outlined by the multi-tier framework (MTF) for measuring the household electricity access. Secondly, for the SHS application, a non-empirical battery lifetime estimation methodology is presented that can be used at the design phase of SHS for comparing the performance of candidate battery choices at hand in the form of battery lifetime. Thirdly, an optimal standalone system size is evaluated for each tier of electrification, taking into account the battery lifetime, temperature impact on SHS performance, power supply availability in terms of the loss of load probability (LLP), and excess PV energy. A genetic algorithm-based multi-objective optimization is performed, giving insights on the delicate interdependencies of the various system metrics like LLP, excess energy, and battery lifetime on the SHS sizing. This exercise concludes that meeting the electricity requirements of tiers 4 and 5 level of electrification is untenable through SHS alone. Consequently, a bottom-up DC microgrid born out of the interconnection of SHS is explored. A modular and scalable architecture for such a bottom-up, interconnected SHS-based architecture is introduced, and the benefits of the microgrid over standalone SHS are quantified in terms of lower battery sizes and the defined system metrics. On modeling the energy sharing between the SHS, it is shown that battery sizing gains of more than 40% could be achieved with inter-connectivity at tier 5 level as compared to standalone SHS to meet the same power availability threshold. Finally, a Geo-Information System (GIS)-based methodology is presented that takes into account the spatial spread of the households while utilizing graph theory-based approaches to arrive at the optimal microgrid topology in terms of network length. The research carried out in this dissertation underlines the technological limitations of SHS in aiming towards universal electrification, while highlighting the benefits of moving towards a bottom-up approach in building (rural) DC microgrids through SHS, which can enable the climb up the so-called electrification ladder.
Original languageEnglish
QualificationDoctor of Philosophy
Awarding Institution
  • Delft University of Technology
  • Bauer, P., Supervisor
  • Zeman, M., Supervisor
  • Qin, Z., Advisor
Award date20 Nov 2019
Print ISBNs978-94-6366-217-8
Publication statusPublished - 2019


  • energy access
  • SDG 7
  • solar home systems
  • solar energy
  • batteries, rural electrification
  • Multi-tier framework
  • GIS,
  • microgrids


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