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ETDs @PUC-Rio
Estatística
Título: INNOVATIVE DECISION MODELS FOR ENERGY COMMERCIALIZATION
Autor: JONAS CALDARA PELAJO
Colaborador(es): LEONARDO LIMA GOMES - Orientador
Catalogação: 13/AGO/2024 Língua(s): ENGLISH - UNITED STATES
Tipo: TEXT Subtipo: THESIS
Notas: [pt] Todos os dados constantes dos documentos são de inteira responsabilidade de seus autores. Os dados utilizados nas descrições dos documentos estão em conformidade com os sistemas da administração da PUC-Rio.
[en] All data contained in the documents are the sole responsibility of the authors. The data used in the descriptions of the documents are in conformity with the systems of the administration of PUC-Rio.
Referência(s): [pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=67542&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=67542&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.67542
Resumo:
In the last decade, the Brazilian electricity sector has faced regulatory and operational challenges due to the need to adapt to changes in the energy matrix, which shows a growing share of intermittent renewable energies, such as solar photovoltaic and wind energy. Additionally, social and environmental restrictions on the construction of new hydroelectric reservoirs require the development of new models for hydrological risk management. This thesis comprises four studies and aims to develop decision support models that contribute to the management of the national interconnected system and the optimization of relevant processes in the sector, considering the current scenario. The first study, by defining a methodology for accessing the parameters of the ECP_G functional, contributes to the innovation and improvement of theoretical models, with practical results for the sector. The second study contributes to the process of seasonalizing the physical guarantee and reveals an optimal strategy that simultaneously maximizes the results of generating agents, preventing reductions in payoffs resulting from individual movements of competitors. The third study proposes a commercialization portfolio optimization model, which allows agents to adequately expose themselves to risk, contributing to more efficient commercial management. Finally, the fourth study presents an operational model for an energy futures clearing house, offering valuable insights for stakeholders interested in establishing such a project in Brazil, where no energy futures clearing house currently exists.
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