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Due to the liberalization of electricity markets, electricity wholesale prices must be regarded as an uncertain parameter within models for investment planning in the energy sector. Another uncertain parameter is the fluctuant generation of renewable power due to the uncertain availability of wind or solar energy. Both parameters play an important role if energy storages are dispatched and evaluated based on market prices. And, as energy storages represent an important option to cope with the increasing share of fluctuant power production, new methods are necessary to evaluate the economical feasibility of different storage types and the effect of support policies for them. Before new evaluation methods incorporating uncertainty can be developed, the stochastic and deterministic characteristics of the uncertain parameters have to be analyzed and modeled adequately, so that simulation data can be produced for the evaluation models. This work concentrates initially on the analysis and modeling of electricity prices and wind power, which contributes the major share within fluctuant generation of renewable power. A combined modeling approach is developed and used for the generation of a large number of time series. The combined modeling of both parameters has the advantage that simulated series contain the so-called "merit order" effect of wind power feed-in on prices. The consideration of this effect is especially important, if integrated plants, consisting of wind power plants and energy storages, are economically evaluated. In the main part of this work, a variety of models are developed for the evaluation of energy storages under uncertainty. These models are then applied to the investment evaluation of a compressed air energy storage (CAES) and pumped storage hydropower (PSHP) plant. The results show that the model, based on stochastic dynamic programming (SDP), delivers the best annual return and thus the highest internal rate of return (IRR) amongst the methodologies which consider electricity prices as uncertain. Finally, an extended version of the SDP model is used for the investment evaluation of an integrated plant, consisting of a CAES and wind power plant. The model results indicate that such a plant is not economically feasible, although a flexibility premium is applied as a further support mechanism. The flexibility mechanism of 15€ =/MWh appears sensible in order to achieve a coordinated operation between the energy storage and wind power plant, but it does not increase the IRR to the level of current PSHP investments. A short analysis with other support mechanisms, such as capacity payments, for flexible power plants shows that the desired IRR level can be achieved for investments in Germany, if the quantum of capacity payments is similar to ones currently paid in Spain.