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Incorporating high-resolution demand and techno-economic optimization to evaluate micro-grids into the Open Source Spatial Electrification Tool (OnSSET)

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posted on 2020-11-30, 14:30 authored by JG Peña Balderrama, S Balderrama Subieta, F Lombardi, N Stevanato, A Sahlberg, Mark HowellsMark Howells, E Colombo, S Quoilin
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.

Funding

Swedish International Development Cooperation Agency (Contribution 75000554-06 Swedish Research Council)

History

School

  • Social Sciences and Humanities

Department

  • Geography and Environment

Published in

Energy for Sustainable Development

Volume

56

Pages

98 - 118

Publisher

Elsevier

Version

  • VoR (Version of Record)

Rights holder

© The Authors

Publisher statement

This is an Open Access Article. It is published by Elsevier under the Creative Commons Attribution 4.0 International Licence (CC BY 4.0). Full details of this licence are available at: https://creativecommons.org/licenses/by/4.0/

Acceptance date

2020-02-29

Publication date

2020-05-18

Copyright date

2020

ISSN

0973-0826

eISSN

2352-4669

Language

  • en

Depositor

Prof Mark Howells. Deposit date: 18 November 2020

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