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| 1 |
ID:
122732
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| Publication |
2013.
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| Summary/Abstract |
In many countries, investments in renewable technologies have been accelerated by fixed feed-in tariffs for electricity from renewable energy sources (RES). While fixed tariffs accomplish this purpose, they lack incentives to align the RES production with price signals. Today, the intermittency of most RES increases the volatility of electricity prices and makes balancing supply and demand more complicated. Therefore, support schemes for RES have to be modified. Recently, Germany launched a scheme which gives wind power operators the monthly choice to either receive a fixed tariff or to risk a - subsidized - access to the wholesale electricity market. This paper quantifies revenues of wind turbines under this new subsidy and analyzes whether, when and where producers may profit. We find that the position of the wind turbine within the country significantly influences revenues in terms of EUR/MWh. The results are important for wind farm operators deciding whether electricity should be sold in the fixed feed-in tariff or in the wholesale market. However, no location is persistently, i.e., in every calendar month of the year, above the average. This limits the effect of the new subsidy scheme on investment locations and long term improvements in the aggregated wind feed-in profile.
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| 2 |
ID:
109317
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| Publication |
2011.
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| Summary/Abstract |
The investment decision on the placement of wind turbines is, neglecting legal formalities, mainly driven by the aim to maximize the expected annual energy production of single turbines. The result is a concentration of wind farms at locations with high average wind speed. While this strategy may be optimal for single investors maximizing their own return on investment, the resulting overall allocation of wind turbines may be unfavorable for energy suppliers and the economy because of large fluctuations in the overall wind power output. This paper investigates to what extent optimal allocation of wind farms in Germany can reduce these fluctuations. We analyze stochastic dependencies of wind speed for a large data set of German on- and offshore weather stations and find that these dependencies turn out to be highly nonlinear but constant over time. Using copula theory we determine the value at risk of energy production for given allocation sets of wind farms and derive optimal allocation plans. We find that the optimized allocation of wind farms may substantially stabilize the overall wind energy supply on daily as well as hourly frequency.
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