2015 IEEE PES Innovative Smart Grid Technologies Latin America (ISGT LATAM) 2015
DOI: 10.1109/isgt-la.2015.7381171
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Geospatial levelized cost of energy in Colombia: GeoLCOE

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Cited by 10 publications
(14 citation statements)
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“…The input parameters are shown in Table 1 for the five most promising clean energy technologies with the values reported in references [16], [19]. These technologies are biomass cogeneration (Bio-cogen), small hydro (S-hydro), wind, solar photovoltaic (PV), and forest biomass (Bio-forest).…”
Section: Model Input Parametersmentioning
confidence: 99%
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“…The input parameters are shown in Table 1 for the five most promising clean energy technologies with the values reported in references [16], [19]. These technologies are biomass cogeneration (Bio-cogen), small hydro (S-hydro), wind, solar photovoltaic (PV), and forest biomass (Bio-forest).…”
Section: Model Input Parametersmentioning
confidence: 99%
“…These technologies are biomass cogeneration (Bio-cogen), small hydro (S-hydro), wind, solar photovoltaic (PV), and forest biomass (Bio-forest). Source: references [16], [19].…”
Section: Model Input Parametersmentioning
confidence: 99%
See 2 more Smart Citations
“…Other platforms like NREL (2014a) consider a more detailed cost breakdown. At the Colombian level, the platform called GeoLCOE computes a geographically based LCOE of new hypothetical generation projects located across the country (Castillo, Mejía & Giraldo, 2015). In fact, the cost breakdown methodology presented in this paper is the underlying approach on which GeoLCOE relies upon (UDEA & UPME, 2015).…”
Section: Introductionmentioning
confidence: 99%