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Incorporating high-resolution demand and techno-economic optimization to evaluate micro-grids into the Open Source Spatial Electrification Tool (OnSSET)
Energy for Sustainable Development ( IF 5.5 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.esd.2020.02.009 J.G. Peña Balderrama , S. Balderrama Subieta , F. Lombardi , N. Stevanato , A. Sahlberg , M. Howells , E. Colombo , S. Quoilin
Energy for Sustainable Development ( IF 5.5 ) Pub Date : 2020-06-01 , DOI: 10.1016/j.esd.2020.02.009 J.G. Peña Balderrama , S. Balderrama Subieta , F. Lombardi , N. Stevanato , A. Sahlberg , M. Howells , E. Colombo , S. Quoilin
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.
更新日期：2020-06-01
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