Summary
In the electric power industry the observed increases of electricity price dynamics combined with the characteristic periodicity of related decision processes have motivated the use of multistage stochastic programming in recent years to provide flexible models for practical applications in the sector. Specifically in power generation and trading the planning process must obey highly complex interrelations between manifold influences. They range from short term price fluctuations as observed in spot markets to long term changes of fundamental influences. Not only changes in the electric supply system itself must be considered, but also the related availability and costs of required fuels. For example, the prices and usability of natural gas in power generation also depend on the existence of respective deployment and distribution systems. Furthermore the electric power sector is exposed to manifold regulatory uncertainties related to the rules imposed by the responsible authorities. Recently environmental issues have become very popular due to the ongoing discussion on climate change. In January 2005 the European Emissions Trading Scheme (EU ETS) has been launched which by many is considered a new key element in efficient electricity market operations. In this paper we will introduce a modeling framework that considers the influence of emission trading on portfolio problems in the electric power sector by applying clean valuation schemes that particularly take fuel costs, emission efficiency in combination with investment possibilities and generation flexibility into account. Sensitivity analysis is performed with respect to changes in technology, volatilities and price scenarios.
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Frauendorfer, K., Güssow, J. (2009). Clean Valuation with Regard to EU Emission Trading. In: Kallrath, J., Pardalos, P.M., Rebennack, S., Scheidt, M. (eds) Optimization in the Energy Industry. Energy Systems. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-88965-6_20
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DOI: https://doi.org/10.1007/978-3-540-88965-6_20
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