|
|
|
Sort Order |
|
|
|
Items / Page
|
|
|
|
|
|
|
| Srl | Item |
| 1 |
ID:
090082
|
|
|
|
|
| Publication |
2009.
|
| Summary/Abstract |
In recent years, the international oil price has fluctuated violently, bringing about huge risk for the international oil trade. In fact, the risk of crude oil and petroleum product imports is different because of the different import origins and prices. Which import risk is lower for China? From the perspective of oil supply security, how should China portfolio crude oil and petroleum product imports to minimize its oil import risk? Using portfolio theory and a diversification index approach, this paper compares and analyzes the supply, price and transport risks of crude oil and petroleum product imports. Our results show that the following: (1) Specific risk (diversification risk) and marine transport risk of China's petroleum product imports are lower than that of crude oil imports. (2) The average rate of return of China's petroleum product imports is higher than that of crude oil imports. Moreover, the average import price variance of petroleum product imports is lower than that of crude oil imports. Thus, the systematic risk (price risk) of petroleum products is lower too. Therefore, from the perspective of oil supply security, China should increase petroleum product imports to decrease its oil import risk.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 2 |
ID:
096627
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Geographic diversification of wind farms can smooth out the fluctuations in wind power generation and reduce the associated system balancing and reliability costs. The paper uses historical wind production data from five European countries (Austria, Denmark, France, Germany, and Spain) and applies the Mean-Variance Portfolio theory to identify cross-country portfolios that minimise the total variance of wind production for a given level of production. Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios. The methodology is then elaborated to derive optimal constrained portfolios taking into account national wind resource potential and transmission constraints and compare them with the projected portfolios for 2020. Such constraints limit the theoretical potential efficiency gains from geographical diversification, but there is still considerable room to improve performance from actual or projected portfolios. These results highlight the need for more cross-border interconnection capacity, for greater coordination of European renewable support policies, and for renewable support mechanisms and electricity market designs providing locational incentives. Under these conditions, a mechanism for renewables credits trading could help aligning wind power portfolios with the theoretically efficient geographic dispersion.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 3 |
ID:
097466
|
|
|
|
|
| Publication |
2010.
|
| Summary/Abstract |
Geographic diversification of wind farms can smooth out the fluctuations in wind power generation and reduce the associated system balancing and reliability costs. The paper uses historical wind production data from five European countries (Austria, Denmark, France, Germany, and Spain) and applies the Mean-Variance Portfolio theory to identify cross-country portfolios that minimise the total variance of wind production for a given level of production. Theoretical unconstrained portfolios show that countries (Spain and Denmark) with the best wind resource or whose size contributes to smoothing out the country output variability dominate optimal portfolios. The methodology is then elaborated to derive optimal constrained portfolios taking into account national wind resource potential and transmission constraints and compare them with the projected portfolios for 2020. Such constraints limit the theoretical potential efficiency gains from geographical diversification, but there is still considerable room to improve performance from actual or projected portfolios. These results highlight the need for more cross-border interconnection capacity, for greater coordination of European renewable support policies, and for renewable support mechanisms and electricity market designs providing locational incentives. Under these conditions, a mechanism for renewables credits trading could help aligning wind power portfolios with the theoretically efficient geographic dispersion.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 4 |
ID:
101368
|
|
|
|
|
| Publication |
2011.
|
| Summary/Abstract |
Standalone levelised cost assessments of electricity supply options miss an important contribution that renewable and non-fossil fuel technologies can make to the electricity portfolio: that of reducing the variability of electricity costs, and their potentially damaging impact upon economic activity. Portfolio theory applications to the electricity generation mix have shown that renewable technologies, their costs being largely uncorrelated with non-renewable technologies, can offer such benefits. We look at the existing Scottish generation mix and examine drivers of changes out to 2020. We assess recent scenarios for the Scottish generation mix in 2020 against mean-variance efficient portfolios of electricity-generating technologies. Each of the scenarios studied implies a portfolio cost of electricity that is between 22% and 38% higher than the portfolio cost of electricity in 2007. These scenarios prove to be mean-variance "inefficient" in the sense that, for example, lower variance portfolios can be obtained without increasing portfolio costs, typically by expanding the share of renewables. As part of extensive sensitivity analysis, we find that Wave and Tidal technologies can contribute to lower risk electricity portfolios, while not increasing portfolio cost.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 5 |
ID:
111061
|
|
|
|
|
| Publication |
2012.
|
| Summary/Abstract |
Ongoing negotiations under the UNFCCC center around the possibilities for stabilization of greenhouse gases at a "safe" level. New energy technologies are assumed to make major contributions to this goal. However, in the light of scientific uncertainty (e.g. about climate sensitivity, feedback effects, etc.), market uncertainty (e.g. fuel price volatility), technological uncertainty (e.g. availability of renewable technology), socio-economic uncertainty (e.g. development of different macroeconomic factors) and policy uncertainty (e.g. about commitment to specific targets and stability of CO2 prices), it is difficult to assess the importance of different technologies in achieving robust long-term climate risk mitigation. One example currently debated in this context is biomass-based energy, which can be used to produce both carbon-neutral electricity and at the same time offer the possibility of "negative emissions" by capturing carbon from biomass combustion at the conversion facility and permanently storing it. In this study, we analyze the impact of uncertainty on investment decision-making at the plant level in a real options valuation framework, and then use the GGI Scenario Database (IIASA, 2009) as a point of departure for deriving optimal technology portfolios across different socio-economic scenarios for a range of stabilization targets, focusing, in particular, on the new, low-emission targets using alternative risk measures.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|