Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques

Detalhes bibliográficos
Autor(a) principal: Arėška, Tomas
Data de Publicação: 2024
Tipo de documento: Dissertação
Idioma: eng
Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Texto Completo: http://hdl.handle.net/10400.5/31099
Resumo: Mestrado Bolonha em Data Analytics for Business
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spelling Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniquesForecasting ModelsTime Series AnalysisWind Energy ForecastingWind SpeedRenewable Energy SectorWind Energy ProductionLithuaniaMestrado Bolonha em Data Analytics for BusinessIn recent years, Lithuania has significantly increased its investment in renewable energy, with a notable emphasis on wind energy. The market leader, Ignitis Group1, has committed over 900 million Euros into renewable energy projects in 2023 alone, showcasing the country's commitment to sustainable energy development. The invasion of Ukraine by Russia has underscored the urgency for Lithuania to achieve energy independence, as reliance on Russian energy imports has ceased and sourcing energy from neighboring countries proves costly. Additionally, the European Green Deal and the push for decarbonization act as further incentives for Lithuania to expand its renewable energy output, ensuring that the Green Deal's targets are met promptly. The ability to accurately forecast wind energy production holds significant importance for energy planning, investment decisions, such as in energy storage solutions, pricing strategies, and ensuring economic stability, rendering this topic highly relevant for Lithuania. This thesis employs forecasting models such as ARIMA, Prophet, and NNAR to perform both short-term and long-term forecasts of wind energy production. Short-term forecasts were conducted on a daily and weekly basis using historical hourly production data. For long-term forecasting, monthly historical data was utilized to construct predictions for the upcoming year. Preliminary time series analyses, including seasonal plots, Augmented Dickey-Fuller (ADF) and Kwiatkowski-Phillips-Schmidt-Shin (KPSS) tests, STL decomposition, and Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) graphs, along with transformation methods like Box-Cox and differencing, were undertaken to prepare the data for forecasting. The findings of this research indicate that the Prophet model significantly outperformed the other models in all forecasting scenarios due to its exceptional ability to capture trends and seasonal fluctuations accurately. The SARIMA model also delivered reasonable forecasts by identifying trends and seasonal patterns. The NNAR model showed decent performance, though it was less effective in capturing the data's movements. Beyond forecasting accuracy, this study offers valuable insights into Lithuania's renewable energy sector, highlighting its current expansion and the broader implications for sustainable energy development in the countryInstituto Superior de Economia e GestãoSobreira, NunoRepositório da Universidade de LisboaArėška, Tomas2024-11-27T01:30:40Z2024-032024-03-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/masterThesisapplication/pdfhttp://hdl.handle.net/10400.5/31099engArėška, Tomas (2024). “Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestãoinfo:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2025-03-17T15:33:26Zoai:repositorio.ulisboa.pt:10400.5/31099Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-29T03:46:57.933946Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
title Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
spellingShingle Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
Arėška, Tomas
Forecasting Models
Time Series Analysis
Wind Energy Forecasting
Wind Speed
Renewable Energy Sector
Wind Energy Production
Lithuania
title_short Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
title_full Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
title_fullStr Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
title_full_unstemmed Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
title_sort Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques
author Arėška, Tomas
author_facet Arėška, Tomas
author_role author
dc.contributor.none.fl_str_mv Sobreira, Nuno
Repositório da Universidade de Lisboa
dc.contributor.author.fl_str_mv Arėška, Tomas
dc.subject.por.fl_str_mv Forecasting Models
Time Series Analysis
Wind Energy Forecasting
Wind Speed
Renewable Energy Sector
Wind Energy Production
Lithuania
topic Forecasting Models
Time Series Analysis
Wind Energy Forecasting
Wind Speed
Renewable Energy Sector
Wind Energy Production
Lithuania
description Mestrado Bolonha em Data Analytics for Business
publishDate 2024
dc.date.none.fl_str_mv 2024-11-27T01:30:40Z
2024-03
2024-03-01T00:00:00Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/masterThesis
format masterThesis
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10400.5/31099
url http://hdl.handle.net/10400.5/31099
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv Arėška, Tomas (2024). “Assessing wind energy production in Lithuania : a comparative analysis of classical and advanced forecasting techniques”. Dissertação de Mestrado. Universidade de Lisboa. Instituto Superior de Economia e Gestão
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
publisher.none.fl_str_mv Instituto Superior de Economia e Gestão
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron:RCAAP
instname_str FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
instacron_str RCAAP
institution RCAAP
reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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