Abstract
Off-grid solar home systems (SHSs) currently constitute a major source of providing basic electricity needs in un(der)-electrified regions of the world, with around 73 million households having benefited from off-grid solar solutions by 2017. However, in and of itself, state-of-the-art SHSs can only provide electricity access with adequate power supply availability up to tier 2, and to some extent, tier 3 levels of the Multi-tier Framework (MTF) for measuring household electricity access. When considering system metrics of loss of load probability (LLP) and battery size, meeting the electricity needs of tiers 4 and 5 is untenable through SHSs alone. Alternatively, a bottom-up microgrid composed of interconnected SHSs is proposed. Such an approach can enable the so-called climb up the rural electrification ladder. The impact of the microgrid size on the system metrics like LLP and energy deficit is evaluated. Finally, it is found that the interconnected SHS-based microgrid can provide more than 40% and 30% gains in battery sizing for the same LLP level as compared to the standalone SHSs sizes for tiers 4 and 5 of the MTF, respectively, thus quantifying the definite gains of an SHS-based microgrid over standalone SHSs. This study paves the way for visualizing SHS-based rural DC microgrids that can not only enable electricity access to the higher tiers of the MTF with lower battery storage needs but also make use of existing SHS infrastructure, thus enabling a technologically easy climb up the rural electrification ladder.
Original language | English |
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Article number | 938 |
Pages (from-to) | 1-22 |
Number of pages | 22 |
Journal | Energies |
Volume | 12 |
Issue number | 5 |
DOIs | |
Publication status | Published - 2019 |
Keywords
- Battery storage
- DC microgrids
- Energy sharing
- Multi-tier framework
- Rural electrification
- Solar home systems
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Electrical power consumption load profiles for households with DC appliances related to Multi-tier framework for household electricity access
Narayan, N. S. (Creator), TU Delft - 4TU.ResearchData, 6 Nov 2018
DOI: 10.4121/UUID:C8EFA325-87FE-4125-961E-9F2684CD2086
Dataset/Software: Dataset