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Application of the Mean-Variance Theory and Resampling Technique for the Italian energy portfolio settlement

机译:平均方差理论和重采采样技术在意大利能源组合沉降中的应用

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The energy planning based on Mean - Variance theory, guides the investors in investment decisions, trying to maximize the return and minimize the risk of investment. However, this theory is based on strong hypotheses and, in addition, input data are often affected by estimation errors. Moreover, this theory determines poor diversification increasing return and risk of the portfolio, and strong variability of the outputs when inputs are varied. In the first part of the paper, the Mean - Variance theory was applied to the energy generation in Italy; in particular, the analysis was on the actual energy mix, but also assuming the use of nuclear technology and taking into account verisimilar improvement, of technologies in the future. On the other hand, in the second part of the paper, a methodology has been applied in order to limit the problems of Mean-Variance theory applied to the energy mix settlement. In particular, the input variables have been calculated using Monte Carlo simulation, in order to reduce the estimation error, and the Resampled Efficiency ? technique has been applied in order to calculate the resulting new "average" efficient frontier. This methodology has been applied either not limiting or limiting the minimum and maximum percentage for every energy generation technology, in order to simulate constraints due, for example, to the technological characteristics of the plant, the availability of the sources and eventually to norms, to the territorial characteristics and to the socio-political choices. The application of Mean - Variance theory allowed to obtain energy portfolio, alternative to the actual, characterized by higher values of expected returns an lower values of risk. It was also shown that the application of the Resampled Efficiency ? technique with data originated with the Monte Carlo simulation effectively tackles the problems of Mean - Variance theory; in this way, the decision maker is helped in making decisions in the energy system policy and development. Thanks to this approach, applied in particular to the Italian energy contest, it was also possible to evaluate the effectiveness of the introduced modifications to the Italian actual energy mix to achieve the 2020 European Energy Directive targets in particular concerning the reduction of CO_2 levels.
机译:基于平均方差理论的能源规划,指导投资者投资决策,试图最大限度地提高返回并尽量减少投资风险。然而,该理论基于强假设,另外,输入数据通常受估计误差的影响。此外,该理论决定了较差的多样化,增加了返回和投资组合的风险,并且当输入变化时输出的强大可变性。在本文的第一部分中,平均方差理论应用于意大利的能量产生;特别是,分析是对实际能量混合,而且假设在未来使用核技术和考虑经验性改善的技术。另一方面,在本文的第二部分中,已经应用了一种方法,以限制适用于能量混合沉降的平均方差理论的问题。特别地,使用Monte Carlo仿真计算输入变量,以减少估计误差和重采样效率?已经应用了技术,以计算所得到的新“平均”高效边疆。这种方法已经应用于每个能源生成技术的最小和最大百分比,以便模拟由于植物的技术特征,源的可用性和最终到规范的限制领土特征和社会政治选择。允许的平均方差理论获得能量组合,实际替代的替代,其特征在于预期更高的预期值返回较低的风险值。还表明应用重采样效率?具有蒙特卡罗模拟的数据的技术有效地解决了平均方差理论的问题;通过这种方式,决策者有助于在能源系统政策和发展中做出决定。由于这种方法,特别适用于意大利能源竞赛,还可以评估对意大利实际能量混合的介绍修改的有效性,以实现2020年欧洲能源指令靶点,特别是关于减少CO_2水平。

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