<?xml version="1.0" encoding="UTF-8"?>
<collection>
<dc:dc xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:invenio="http://invenio-software.org/elements/1.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://www.openarchives.org/OAI/2.0/oai_dc/ http://www.openarchives.org/OAI/2.0/oai_dc.xsd"><dc:identifier>doi:10.1016/j.enconman.2019.06.057</dc:identifier><dc:language>eng</dc:language><dc:creator>Dufo López, Rodolfo</dc:creator><dc:creator>Champier, Daniel</dc:creator><dc:creator>Gibout, Stephan</dc:creator><dc:creator>Lujano-Rojas, Juan M.</dc:creator><dc:creator>Domínguez-Navarro, José A.</dc:creator><dc:title>Optimisation of off-grid hybrid renewable systems with thermoelectric generator</dc:title><dc:identifier>ART-2019-112735</dc:identifier><dc:description>This paper shows, for the  rst time, the optimisation of the electrical supply in o -grid systems by means of hybrid renewable systems (photovoltaic + wind + battery + fossil fuel) including thermoelectric generator (which source of heat is the exhaust gas of a stove used for cooking or heating).
The objective is to minimise the net present cost. An advanced battery model and the accurate calculation of the net present cost (including all the costs during the system lifetime) are considered in the optimisation of this kind of systems. The standard simpli ed model of the thermoelectric generator is used, as more complex models cannot be used in an optimisation framework, where hundreds or thousands of di erent cases must be simulated (each combination of components must be simulated at least during one year, in 1-min steps). The optimization is carried out e ciently by means of genetic algorithms.
The method has been applied in the optimisation of two cases of low consumption o -grid households (Cambodia and Norway). Thermoelectric generator (costing €8/W) is part of the optimal solution in the case of Norway. In Cambodia, to be part of the optimal system, acquisition cost of the thermoelectric generator should be reduced by 25%.</dc:description><dc:date>2019</dc:date><dc:source>http://zaguan.unizar.es/record/131273</dc:source><dc:doi>10.1016/j.enconman.2019.06.057</dc:doi><dc:identifier>http://zaguan.unizar.es/record/131273</dc:identifier><dc:identifier>oai:zaguan.unizar.es:131273</dc:identifier><dc:relation>info:eu-repo/grantAgreement/ES/MEC/PRX18-00030</dc:relation><dc:identifier.citation>ENERGY CONVERSION AND MANAGEMENT 196 (2019), 1051-1067</dc:identifier.citation><dc:rights>All rights reserved</dc:rights><dc:rights>http://www.europeana.eu/rights/rr-f/</dc:rights><dc:rights>info:eu-repo/semantics/closedAccess</dc:rights></dc:dc>

</collection>