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| 1 |
ID:
150031
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| Summary/Abstract |
In this paper, we identify and analyze parameters that determine the profitability of wind power operators in the German market premium model. Based on an empirical analysis of different German wind power profiles from 2007 to mid-2012, we are able to show that the profitability significantly depends on the correlation of the wind power portfolio with the overall wind power feed-in and prediction error in Germany. Significant differences between the wind forecast errors clearing cost of the analyzed portfolios can be identified. Our analysis shows that a wind power operator would profit in most cases from a reduced forecast error, which could be achieved through an improved forecast model and an increased share of the intraday cleared error. Furthermore significant locational portfolio advantages and disadvantages can be identified when comparing the different market values. In general, the empirical analysis shows that a premium of 3.5 €/MWh is suitable to cover the cost of an imperfect forecast. Taking further into account that for 2012 a premium of 12 €/MWh was granted; the direct marketing option can be evaluated as highly attractive, which is furthermore indicated by the rapid increase of the directly marketed wind power and photovoltaic generation.
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| 2 |
ID:
125410
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| Publication |
2013.
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| Summary/Abstract |
Wind power generation and its impacts on electricity prices has strongly increased in the EU. Therefore, appropriate mark-to-market evaluation of new investments in wind power and energy storage plants should consider the fluctuant generation of wind power and uncertain electricity prices, which are affected by wind power feed-in (WPF). To gain the input data for WPF and electricity prices, simulation models, such as econometric models, can serve as a data basis.
This paper describes a combined modeling approach for the simulation of WPF series and electricity prices considering the impacts of WPF on prices based on an autoregressive approach. Thereby WPF series are firstly simulated for each hour of the year and integrated in the electricity price model to generate an hourly resolved price series for a year. The model results demonstrate that the WPF model delivers satisfying WPF series and that the extended electricity price model considering WPF leads to a significant improvement of the electricity price simulation compared to a model version without WPF effects. As the simulated series of WPF and electricity prices also contain the correlation between both series, market evaluation of wind power technologies can be accurately done based on these series.
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