Título: | RISK ANALYSIS APPLIED TO SELECT PRIMARY ENERGY SOURCES FOR POWER GENERATION IN BRAZIL | |||||||
Autor: |
JAIR ARONE MAUES |
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Colaborador(es): |
ELOI FERNANDEZ Y FERNANDEZ - Orientador |
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Catalogação: | 14/JAN/2009 | Língua(s): | PORTUGUESE - BRAZIL |
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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. |
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Referência(s): |
[pt] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=12964&idi=1 [en] https://www.maxwell.vrac.puc-rio.br/projetosEspeciais/ETDs/consultas/conteudo.php?strSecao=resultado&nrSeq=12964&idi=2 |
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DOI: | https://doi.org/10.17771/PUCRio.acad.12964 | |||||||
Resumo: | ||||||||
The work compares current approaches for evaluating and planning
Brazilian energy mixes for future power generation, based
not only on energy cost
components contribution to a portfolio, but on their
contribution to portfolio risk,
as well. Energy planners have traditionally used least-cost
as a basis for
generating capacity additions, understating the true value
of non traditional
renewable technologies for decreasing risk. This project
applies widely accepted
finance theory, Mean-Variance Portfolio Theory, developed by
Harry Markowitz,
to provide an economic basis for selecting alternative
generating scenarios. First,
Brazil`s expected future generating mix for 2030 as
predicted by Empresa de
Pesquisa Energética in its 2030 Brazilian Power Planning,
published in 2006, is
evaluated. This mix is referred to as the reference EPE
scenario. The risk-return
properties of Brazil`s expected EPE mix for the year 2030 is
compared to other
possible mixes on the projected efficient frontier. The
model finds solutions that
are superior to the EPE mix in that they reduce risk or cost
or both, while
including a greater share of wind and biomass from sugar
cane in the mix. The
basic findings of this analysis seem quite robust, and do
not materially change the
shape of the efficient frontier, where it is technically
feasible, even when the risk
parameter estimates and cost covariations are changed
significantly in the
sensitivity analysis.
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