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ETDs @PUC-Rio
Estatística
Título: A BLOCKCHAIN BASED MODEL FOR THE OFFER OF RENEWABLE ENERGY CERTIFICATES UNDER UNCERTAINTY AND FLEXIBILITY
Autor: NAIELLY LOPES MARQUES
Colaborador(es): LUIZ EDUARDO TEIXEIRA BRANDAO - Orientador
Catalogação: 24/ABR/2019 Língua(s): PORTUGUESE - BRAZIL
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=37815&idi=1
[en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=37815&idi=2
DOI: https://doi.org/10.17771/PUCRio.acad.37815
Resumo:
Reducing pollution and greenhouse gas emissions has been the focus of a major global effort. In this context, Renewable Energy Certificates (RECs) are important as they provide incentives for changes in the energy matrix, towards the adoption of sustainable practices. Given the growth of this market and the characteristics of RECs, one of the potential drivers of their adoption is the blockchain network protocol. In this research, we analyze three autonomous models for issuing and selling in the blockchain of REC based tokens for the renewable energy generator. In all three models, the generator has the option to invest now or in one year for the right to issue RECs and offer them through quarterly sales auctions. In the first model, we assume that the token price is fixed following a stable coin concept. In the second model, we consider that the price follows an inverse demand function subject to stochastic shocks. Finally, in the third model, the demand for RECs is uncertain and the purpose is to maximize the generator s profit. Through a numerical application, we verify the validity of the models and conclude, considering the parameters adopted, that the generator should invest in the second model, since it was the one with the highest NPV (60,992.70 real). However, if the demand volatility is less than 20.00 percent, the optimal model for the generator is the first model. The main contribution of this work is to analyze the performance dynamics of digital products under uncertainty.
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