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dc.contributor.advisorBogas Gálvez, Juan-
dc.contributor.authorRoa Prieto, Miguel-
dc.contributor.otherUniversidad Pontificia Comillas, Escuela Técnica Superior de Ingeniería (ICAI)es_ES
dc.date.accessioned2019-01-23T15:33:22Z-
dc.date.available2019-01-23T15:33:22Z-
dc.date.issued2018-
dc.identifier.urihttp://hdl.handle.net/11531/34813-
dc.descriptionMaster in the Electric Power Industryes_ES
dc.description.abstractIntroduction This Project tries to forecast as precisely as possible the energy prices in the Iberian Market between the years 2020 and 2030, taking into account the European goal of reducing the emissions and the evolution of the different technologies in order to do so. Therefore, this project will consider many factors: demand evolution, electricity generation technologies maturity, energy policy evolution, public opinion, etc. Some factors evolution are extremely uncertain, so, some of them are inputs for the model: efficiency rate, coal plants dismantlement, political decision of renewing nuclear plants operation license, CO2 price rate and hydro management horizon. Methodology The forecast of electricity prices is carried out hourly, following the next steps: Firstly, the demand is estimated based on the historical profile data and updated according to expected evolution of GDP, population and efficiency. Then, the need of RES capacity to accomplish 2030’s polluting emission objectives as well as satisfying demand is estimated. This is done by means of an iterative generation dispatch process only for 2030, starting the dispatch with capacity already installed in 2020. The capacity to be installed increases until carbon dioxide emission limit is not surpassed. The new capacity is allocated to one or another technology depending on expected availability factors at critical hours, which are calculated based on historical data. Once the new capacity to be installed during the next decade is known, the model considers a progressive deployment of the capacity, installing every year the same amount. At this point, the dispatch for all hours of the decade 20-30 is computed. Dispatching methodology is based on the lowest cost merit order. Finally, hourly electricity prices are calculated based on previous generation dispatch. The electricity price is the cost of producing the most expensive MWh dispatched. Results and conclusions Several scenarios are analysed for different levels of demand efficiency, plants dismantlement and CO2 price. Model results show that political decisions to be taken in the near future in terms of RES support mechanisms design and nuclear and coal plants dismantlement; added to efficiency evolution are extremely critical regarding electricity prices and RES capacity needs. Figure below shows different efficiency scenarios of RES capacity to be installed before 2030 considering that nuclear plants renew their license for 20 years more and the contrary.es_ES
dc.format.mimetypeapplication/pdfes_ES
dc.language.isoenes_ES
dc.rightsAttribution-NonCommercial-NoDerivs 3.0 United States*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/3.0/us/*
dc.subject33 Ciencias tecnológicases_ES
dc.subject3322 Tecnología energéticaes_ES
dc.subject332205 Fuentes no convencionales de energíaes_ES
dc.subject53 Ciencias económicases_ES
dc.subject5312 Economía sectoriales_ES
dc.subject531205 Energíaes_ES
dc.titleForecast of schedule of different technologies and prices for the period 2020 to 2030 for the Iberian energy marketes_ES
dc.typeinfo:eu-repo/semantics/masterThesises_ES
dc.rights.accessRightsinfo:eu-repo/semantics/openAccesses_ES
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