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dc.contributor.advisorStadler, Micheal
dc.contributor.advisorFerreira Cardoso, Gonçalo
dc.contributor.authorSchittekatte, Tim
dc.contributor.otherUniversidad Pontificia Comillas, Escuela Técnica Superior de Ingeniería (ICAI)es_ES
dc.date.accessioned2015-11-05T13:23:42Z
dc.date.available2015-11-05T13:23:42Z
dc.date.issued2015
dc.identifier.urihttp://hdl.handle.net/11531/4297
dc.descriptionMaster in the Electric Power Industryes_ES
dc.description.abstractIn this research the impact of solar irradiation variability and battery prices on costoptimal distributed energy resource (DER) investments is analyzed. A novel methodology is proposed to capture the impact on power demand charges caused by moving clouds in microgrids where photovoltaic (PV) arrays, electrochemical energy storage and generators are considered. This is done using a statistical approach to decouple accounting of energy and power demand economics, and allows events of di erent time lengths to be simultaneously analyzed. The methodology is implemented in the Distributed Energy Resources Customer Adoption Model (DER-CAM), and four case studies are performed. In DER-CAM, a state of the art mixed integer linear model used to nd cost- and CO2- optimal DER portfolios of energy supply in decentralized energy systems, PV output is calculated using monthly average-hourly solar irradiation data. This approach fails to capture the e ect of fast moving clouds and may sometimes lead to inaccurate results. The methodology introduced in this work estimates the variability of PV output and the resulting impact on power demand charges for di erent con dence levels taking into account that existing energy storage may o set drops in PV output if su ciently charged, or that fast-ramping generator units may also be used for the same purpose. This formulation is embedded in the investment decision process, and is re ected in the optimal DER portfolio provided by DER-CAM. Results obtained in the case studies suggest that in previous DER-CAM formulations the optimal capacity of PV was overestimated in cases where storage capacity was not su cient to compensate for drops in PV output. Also it was found that the optimal capacity of on-site generators might have been slightly underestimated in some cases. The new model formulation depicts the economic value of PV more accurately while e ectively capturing the synergic economic bene ts of PV paired with electric storage.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenes_ES
dc.subject33 Ciencias tecnológicases_ES
dc.subject3306 Ingeniería y tecnología eléctricaes_ES
dc.subject330609 Transmisión y distribuciónes_ES
dc.titleThe impact of stochastic variability in insolation and capital cost of batteries on optimal microgrid designes_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
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