Incorporating high-resolution demand and techno-economic optimization to evaluate micro-grids into the Open Source Spatial Electrification Tool (OnSSET)
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Published version
Author(s)
Type
Journal Article
Abstract
For decades, electrification planning in the developing world has often focused on extending the national grid to increase electricity access. This article draws attention to the potential complementary role of decentralized alternatives – primarily micro-grids – to address universal electricity access targets. To this aim, we propose a methodology consisting of three steps to estimate the LCOE and to size micro-grids for large-scale geo-spatial electrification modelling. In the first step, stochastic load demand profiles are generated for a wide range of settlement archetypes using the open-source RAMP model. In the second step, stochastic optimization is carried by the open-source MicroGridsPy model for combinations of settlement size, load demand profiles and other important techno-economic parameters influencing the LCOE. In the third step, surrogate models are generated to automatically evaluate the LCOE using a multivariate regression of micro-grid optimization results as a function of influencing parameters defining each scenario instance. Our developments coupled to the OnSSET electrification tool reveal an important increase in the cost-competitiveness of micro-grids compared to previous analyses.
Date Issued
2020-06-01
Date Acceptance
2020-02-29
Citation
Energy for Sustainable Development: the journal of the international energy initiative, 2020, 56, pp.98-118
ISSN
0973-0826
Publisher
Elsevier
Start Page
98
End Page
118
Journal / Book Title
Energy for Sustainable Development: the journal of the international energy initiative
Volume
56
Copyright Statement
© 2020 The Authors. Published by Elsevier Inc. on behalf of International Energy Initiative. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
License URL
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000544062200009&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Subjects
Science & Technology
Technology
Green & Sustainable Science & Technology
Energy & Fuels
Science & Technology - Other Topics
LOAD PROFILES
REANALYSIS
SYSTEMS
GIS
MAP
Publication Status
Published
Date Publish Online
2020-05-18