Optimal design of a photovoltaic station using Markov and energy price modelling
Descripción del Articulo
As the fight against anthropogenic global warming increases, photovoltaic (PV) systems, which are a type of renewable energy, are increasingly being considered. In order to use PV systems, it is necessary to develop methods to optimize their configuration, that is, the optimal number of PV modules a...
| Autor: | |
|---|---|
| Formato: | tesis de maestría |
| Fecha de Publicación: | 2023 |
| Institución: | Pontificia Universidad Católica del Perú |
| Repositorio: | PUCP-Tesis |
| Lenguaje: | inglés |
| OAI Identifier: | oai:tesis.pucp.edu.pe:20.500.12404/24949 |
| Enlace del recurso: | http://hdl.handle.net/20.500.12404/24949 |
| Nivel de acceso: | acceso abierto |
| Materia: | Sistemas de energía fotovoltaica Procesos de Markov Energía renovable https://purl.org/pe-repo/ocde/ford#2.00.00 |
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Optimal design of a photovoltaic station using Markov and energy price modelling |
| title |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| spellingShingle |
Optimal design of a photovoltaic station using Markov and energy price modelling Salazar Márquez, Marcio Boris Sistemas de energía fotovoltaica Procesos de Markov Energía renovable https://purl.org/pe-repo/ocde/ford#2.00.00 |
| title_short |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| title_full |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| title_fullStr |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| title_full_unstemmed |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| title_sort |
Optimal design of a photovoltaic station using Markov and energy price modelling |
| author |
Salazar Márquez, Marcio Boris |
| author_facet |
Salazar Márquez, Marcio Boris |
| author_role |
author |
| dc.contributor.advisor.fl_str_mv |
Tafur Sotelo, Julio César |
| dc.contributor.author.fl_str_mv |
Salazar Márquez, Marcio Boris |
| dc.subject.es_ES.fl_str_mv |
Sistemas de energía fotovoltaica Procesos de Markov Energía renovable |
| topic |
Sistemas de energía fotovoltaica Procesos de Markov Energía renovable https://purl.org/pe-repo/ocde/ford#2.00.00 |
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https://purl.org/pe-repo/ocde/ford#2.00.00 |
| description |
As the fight against anthropogenic global warming increases, photovoltaic (PV) systems, which are a type of renewable energy, are increasingly being considered. In order to use PV systems, it is necessary to develop methods to optimize their configuration, that is, the optimal number of PV modules and inverters. The objectives are to examine the optimization of PVs subject to not only the operational constraints but also the failure and repair events of PV inverters up to 100 kW, while minimizing the effective levelized cost of energy. To achieve this, using Markov modelling, a new energy price model that considers the current prices of the PV inverters is developed as part of a new optimization framework. A case study considering six real PV inverters is developed to show the effectiveness of the framework. In addition, real data from a reference PV station in Germany is used to calculate the average hours per day that a panel generates its rated power to consider the geographical location, temperature and number of sunny days in the given region. Unlike previous work, local and global optimal solutions are found using PV inverters in the range of 15 kW to 100 kW. Therefore, the new findings of this study will be considered in the future, for example, when considering the failure and repair events of PV modules. |
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2023 |
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2023-05-10T02:47:28Z |
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2023-05-10T02:47:28Z |
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2023 |
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2023-05-09 |
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info:eu-repo/semantics/masterThesis |
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masterThesis |
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http://hdl.handle.net/20.500.12404/24949 |
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http://hdl.handle.net/20.500.12404/24949 |
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eng |
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eng |
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SUNEDU |
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http://creativecommons.org/licenses/by/2.5/pe/ |
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Tafur Sotelo, Julio CésarSalazar Márquez, Marcio Boris2023-05-10T02:47:28Z2023-05-10T02:47:28Z20232023-05-09http://hdl.handle.net/20.500.12404/24949As the fight against anthropogenic global warming increases, photovoltaic (PV) systems, which are a type of renewable energy, are increasingly being considered. In order to use PV systems, it is necessary to develop methods to optimize their configuration, that is, the optimal number of PV modules and inverters. The objectives are to examine the optimization of PVs subject to not only the operational constraints but also the failure and repair events of PV inverters up to 100 kW, while minimizing the effective levelized cost of energy. To achieve this, using Markov modelling, a new energy price model that considers the current prices of the PV inverters is developed as part of a new optimization framework. A case study considering six real PV inverters is developed to show the effectiveness of the framework. In addition, real data from a reference PV station in Germany is used to calculate the average hours per day that a panel generates its rated power to consider the geographical location, temperature and number of sunny days in the given region. Unlike previous work, local and global optimal solutions are found using PV inverters in the range of 15 kW to 100 kW. Therefore, the new findings of this study will be considered in the future, for example, when considering the failure and repair events of PV modules.Im Rahmen des Kampfes gegen die anthropogene Erderwärmung werden zunehmend Photovoltaikanlagen (PV-Anlagen) in Betracht gezogen, welche zu den erneuerbaren Energien zählen. Um PV-Anlagen nutzen zu können, müssen Methoden zur Optimierung ihrer Konfiguration, d. h. der optimalen Anzahl von PV-Modulen und Wechselrichtern, entwickelt werden. Ziel dieser Arbeit ist es, die Optimierung von PV-Anlagen zu untersuchen, wobei nicht nur die betrieblichen Randbedingungen, sondern auch die Ausfall- und Reparaturereignisse von PV-Wechselrichtern bis zu 100 kW berücksichtigt werden, um dabei die effektiven Stromgestehungskosten zu minimieren. Um dies zu erreichen, wird ein neues Energiepreismodell entwickelt, das die aktuellen Preise der PV-Wechselrichter, sowie die Markoff-Modellierung als Teil eines neuen Optimierungsrahmens berücksichtigt. Anhand einer Fallstudie unter Berücksichtigung von sechs realen PV-Wechselrichtern wird die Wirksamkeit des Rahmens aufgezeigt. Außerdem werden reale Daten einer Referenz-PV-Anlage in Deutschland verwendet, um die durchschnittlichen Stunden pro Tag zu berechnen, in denen ein Modul seine Nennleistung erzeugt. Dazu werden die geografische Lage, die Temperatur und die Anzahl der Sonnentage in der jeweiligen Region berücksichtigt. Im Gegensatz zu früheren Arbeiten werden lokal und global optimale Lösungen mit PV-Wechselrichtern im Bereich von 15 kW bis 100 kW gefunden. Daher können die neuen Erkenntnisse dieser Studie in Zukunft beispielsweise bei der Betrachtung von Ausfall- und Reparaturereignissen von PV-Modulen berücksichtigt werden.Ante la creciente lucha contra el calentamiento global antropogénico, los sistemas fotovoltaicos, que son un tipo de energía renovable, están siendo cada vez más considerados. Para usar sistemas fotovoltaicos, es necesario desarrollar métodos para optimizar su configuración, es decir, el número óptimo de módulos e inversores fotovoltaicos. Los objetivos de esta tesis son examinar la optimización de los sistemas fotovoltaicos sujetos, no sólo a las restricciones operativas, sino también a los eventos de falla y reparación de los inversores fotovoltaicos de hasta 100 kW, mientras se minimiza el costo efectivo nivelado de la energía. Para lograrlo, empleando el modelo de Márkov, se desarrolla un nuevo modelo del precio de la energía que considera los costos actuales de los inversores fotovoltaicos como parte de un nuevo esquema de optimización. Se desarrolla un caso de estudio considerando seis inversores fotovoltaicos reales para mostrar la efectividad del esquema. Asimismo, se utilizan datos reales de una estación fotovoltaica de referencia en Alemania para calcular el promedio de horas al día en que un panel genera su potencia nominal teniendo en cuenta la ubicación geográfica, la temperatura y el número de días soleados de la región. A diferencia de trabajos anteriores, se encuentran soluciones locales y globales óptimas empleando inversores fotovoltaicos en el rango de 15 kW a 100 kW. Por lo tanto, los nuevos hallazgos de este estudio se tomarán en cuenta en el futuro, por ejemplo, cuando se contemplen los eventos de falla y reparación de los módulos fotovoltaicos.engPontificia Universidad Católica del PerúPEinfo:eu-repo/semantics/openAccesshttp://creativecommons.org/licenses/by/2.5/pe/Sistemas de energía fotovoltaicaProcesos de MarkovEnergía renovablehttps://purl.org/pe-repo/ocde/ford#2.00.00Optimal design of a photovoltaic station using Markov and energy price modellinginfo:eu-repo/semantics/masterThesisreponame:PUCP-Tesisinstname:Pontificia Universidad Católica del Perúinstacron:PUCPSUNEDUMaestro en Ingeniería MecatrónicaMaestríaPontificia Universidad Católica del Perú. Escuela de Posgrado.Ingeniería Mecatrónica06470028https://orcid.org/0000-0003-3415-196944646347713167Villota Cerna, Elizabeth RoxanaTafur Sotelo, Julio CesarShardt Wolchuk, Yuri AndriGabash, Aousshttps://purl.org/pe-repo/renati/level#maestrohttps://purl.org/pe-repo/renati/type#tesisORIGINALSALAZAR_MARQUEZ_MARCIO_OPTIMAL_DESIGN_PHOTOVOLTAIC.pdfSALAZAR_MARQUEZ_MARCIO_OPTIMAL_DESIGN_PHOTOVOLTAIC.pdfTexto completoapplication/pdf2121058https://tesis.pucp.edu.pe/bitstreams/cf8921a9-1244-4deb-8d41-ebc9a585b180/download7f7ba40d75aca2f37accd4c80288f884MD51trueAnonymousREADSALAZAR_MÁRQUEZ_MARCIO_BORIS_T.pdfSALAZAR_MÁRQUEZ_MARCIO_BORIS_T.pdfReporte de originalidadapplication/pdf9809752https://tesis.pucp.edu.pe/bitstreams/5bef87f0-72d1-4c42-8804-8bfd059ae6e0/download478d59c9387572e7d33ba2652d05972cMD52falseAnonymousREAD2500-01-01CC-LICENSElicense_rdflicense_rdfapplication/rdf+xml; charset=utf-8914https://tesis.pucp.edu.pe/bitstreams/d8973c10-595f-4cea-840d-1280133faf15/download5a4ffbc01f1b5eb70a835dac0d501661MD53falseAnonymousREADLICENSElicense.txtlicense.txttext/plain; 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