For carbon capture and storage (CCS) to be a truly effective option in our efforts to mitigate climate change, it must be sustainable. That means that CCS must deliver consistent environmental and social benefits which exceed its costs of capital, energy and operation; it must be protective of the environment and human health over the long term; and it must be suitable for deployment on a significant scale. CCS is one of the more expensive and technically challenging carbon emissions abatement options available, and CCS must first and foremost be considered in the context of the other things that can be done to reduce emissions, as a part of an overall optimally efficient, sustainable and economic mitigation plan. This elevates the analysis beyond a simple comparison of the cost per tonne of CO2 abated—there are inherent tradeoffs with a range of other factors (such as water, NOx, SOx, biodiversity, energy, and human health and safety, among others) which must also be considered if we are to achieve truly sustainable mitigation. The full life-cycle cost of CCS must be considered in the context of the overall social, environmental and economic benefits which it creates, and the costs associated with environmental and social risks it presents. Such analysis reveals that all CCS is not created equal. There is a wide range of technological options available which can be used in a variety of industries and applications—indeed CCS is not applicable to every industry. Stationary fossil-fuel powered energy and large scale petroleum industry operations are two examples of industries which could benefit from CCS. Capturing and geo-sequestering CO2 entrained in natural gas can be economic and sustainable at relatively low carbon prices...
The shareholders of E&P companies evaluate the future performance of these companies in terms of multiple performance attributes. Hence, E&P decision makers have the task of allocating limited resources to available project proposals to deliver the best performance on these various attributes. Additionally, the performance of these proposals on these attributes is uncertain and the attributes of the various proposals are usually correlated. As a result of the above, the E&P portfolio optimisation decision setting is characterised by multiple attributes with uncertain future performance.
Most recent contributions in the E&P portfolio optimisation arena seek to adapt modern financial portfolio theory concepts to the E&P project portfolio selection problem. These contributions generally focus on understanding the tradeoffs between risk and return for the attribute NPV while acknowledging the presence of correlation among the assets of the portfolio. The result is usually an efficient frontier where one objective is set over the expected value of the NPV and the other is set over a risk metric calculated from the same attribute where, typically, the risk metric has a closed form solution (e.g.,
variance, standard deviation, semi-standard deviation). However...
Fonte: Centro Comum de Pesquisa da Comissão EuropéiaPublicador: Centro Comum de Pesquisa da Comissão Européia
Tipo: Contributions to ConferencesFormato: Printed
Relevância na Pesquisa
The introduction of renewable energies and as one example solar electricity into existing energy supplies reduces the supply risk and can, despite a higher kWh generating cost lower the overall costs of an optimised energy portfolio mix. This paper will give an overview about the societal and economic benefits the implementation of solar photovoltaic systems are providing for society.; JRC.H.8-Renewable energies
Mestrado em Finanças; Este trabalho visa avaliar o contributo de uma gestão activa comparativamente a uma gestão passiva no desempenho de determinado portfolio, composto por acções do PSI20. A gestão activa teve em conta uma carteira de acções determinada com base no modelo de Markowitz, enquanto que, a gestão passiva tem por base uma carteira composta por acções com proporções iguais. Na gestão activa, as proporções a investir nos activos foram revistas tendo em conta a evolução do mercado, numa base mensal. No entanto, a determinação das ponderações óptimas teve em atenção diferentes cenários em "sistema de janela". Como segundo objectivo, foi definido o estudo do impacto dos custos de intermediação financeira na performance de ambos os portfolios anteriores. Foram utilizados títulos cotados do PSI 20 durante um período de 11 anos (entre 1 de Janeiro de 1996 e 31 de Dezembro de 2006). As conclusões mostram que não compensa optar por uma gestão activa face a uma gestão passiva, quando a carteira objecto da gestão seja composta por activos cotados no PSI20. Para esta conclusão contribuem dois factores: os custos de intermediação financeira e os erros cometidos na estimação dos principais inputs para cálculo das ponderações óptimas da carteira. A melhor opção revelou-se no investimento no índice de Mercado (PSI 20).; The goal of this Thesis is to evaluate the contribution of an active management versus passive management to the portfolio performance...
At the heart of the analytical pipeline of a modern quantitative
insurance/reinsurance company is a stochastic simulation technique for
portfolio risk analysis and pricing process referred to as Aggregate Analysis.
Support for the computation of risk measures including Probable Maximum Loss
(PML) and the Tail Value at Risk (TVAR) for a variety of types of complex
property catastrophe insurance contracts including Cat eXcess of Loss (XL), or
Per-Occurrence XL, and Aggregate XL, and contracts that combine these measures
is obtained in Aggregate Analysis.
In this paper, we explore parallel methods for aggregate risk analysis. A
parallel aggregate risk analysis algorithm and an engine based on the algorithm
is proposed. This engine is implemented in C and OpenMP for multi-core CPUs and
in C and CUDA for many-core GPUs. Performance analysis of the algorithm
indicates that GPUs offer an alternative HPC solution for aggregate risk
analysis that is cost effective. The optimised algorithm on the GPU performs a
1 million trial aggregate simulation with 1000 catastrophic events per trial on
a typical exposure set and contract structure in just over 20 seconds which is
approximately 15x times faster than the sequential counterpart. This can
sufficiently support the real-time pricing scenario in which an underwriter
analyses different contractual terms and pricing while discussing a deal with a
client over the phone.; Comment: Proceedings of the Workshop at the International Conference for High