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X-WR-CALNAME;VALUE=TEXT:Global Renewable Levelized Cost of Electricity (LCOE)—Including Socio-Economic Factors in Assessment of Resource Potential
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SUMMARY:Global Renewable Levelized Cost of Electricity (LCOE)—Including Socio-Economic Factors in Assessment of Resource Potential
DESCRIPTION:<p>	<strong><!--break-->A Harvard-China Project Research Seminar with Xiaoming Kan, Department of Space, Earth and Environment, Chalmers University of Technology, Sweden</strong></p><p>	<strong>Abstract: </strong>Global renewable energy resource assessments have been criticized for not including country-specific economic and socio-political conditions. Here, we take steps towards a more realistic assessment of renewable resource potential by incorporating social considerations for land-use requirements, heterogenous discount rate and electricity demand into the LCOE metric. We introduce three metrics to assess the renewable resource potential: Renewable LCOE, Renewable LCOE with country-dependent discount rate and Renewable LCOE available for export. The latter measures a country's potential for renewable self-sufficiency and export. We calculate and map these matrics for most countries in the world. Our findings show that the economic and socio-political factors greatly influence the assessment of cost and self-sufficiency. Countries that stand out as having large potential for export of renewable energy include the US, Australia and Saudi Arabia. The work that we present here may be used for further analysis of future energy security of supply and geopolitics.</p><p>	<strong>Xiaoming Kan</strong>'s research focuses on modelling of policies and investments for a large-scale introduction of variable renewable power production, which is part of ENSYSTRA (energy systems in transition) training network. The main objective of his research is to evaluate investments and variation management strategies that are cost-effective to use in a renewable power system and assess policies that can foster such a system. His research interests lie in the field of modelling of energy systems and energy markets.</p><h4>	<span style="background-color:#ffff00"><a href="https://harvard.zoom.us/meeting/register/tJMvfu6hqTkoGtajy9_db2U6D72Vn5f1DR3H" target="_blank" title="">REGISTER HERE</a></span><br>Zoom link will be sent to those that register</h4><p>	<em>Sponsored by Harvard-China Project, Harvard Paulson School of Engineering and Applied Sciences</em>.</p><p>	 </p>
LOCATION:Virtual - Zoom registration required
STATUS:CONFIRMED
DTSTART:20221130T200000Z
DTEND:20221130T210000Z
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