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Design and analysis of solar PV based low-power low-voltage DC microgrid architectures for rural electrification

Authors :
Sana Fazal
Hassan Abbas Khan
Muhammad Hamza
Mashood Nasir
Muhammad Shehroz
Source :
2017 IEEE Power & Energy Society General Meeting.
Publication Year :
2017
Publisher :
IEEE, 2017.

Abstract

Over 1.3 billion people worldwide primarily in Africa and South-East Asia have no access to electricity. Electrification of these remote rural regions through national power grids is largely unviable low due to i) a high infrastructure cost and ii) limited power generation capacity in many countries. Therefore, low-power, low-voltage, solar photovoltaic (PV) based DC microgrids are becoming very popular in these regions. Many of these low voltage solar powered DC microgrids are based on central generation and central storage with distribution efficiencies typically ranging from 60% to 80%. Therefore, it is important to design better architectures to attain the highest possible efficiency within system constraints. In this work, we analyze three possible distribution architectures and evaluate their operational efficiency with regards to typical spatial village orientations in many developing countries. These include C-Architecture, Cluster-Architectures and O-Architecture with maximum distribution efficiencies of 83.5%, 91.6% and 95.6%, respectively for a typical 40-house village at 24V DC distribution utilizing 10 AWG conductors. Based upon the comparative analysis in this work, an efficient distribution architecture of a village can be proposed in accordance with its orientation (arrangement of houses) to achieve a higher operational efficiency and a reduced upfront cost. This work will typically be useful in the design and implementation of new low-power low-voltage microgrid systems as well as in upgradation of existing microgrid systems to maximize their utility.

Details

Database :
OpenAIRE
Journal :
2017 IEEE Power & Energy Society General Meeting
Accession number :
edsair.doi...........4e6e2669d1bc72f936ca99755fb822ca
Full Text :
https://doi.org/10.1109/pesgm.2017.8274134