The costs of electricity systems with a high share of fluctuating renewables - a stochastic investment and dispatch optimization model for Europe - Stephan Nagl; Michaela Fürsch; Dietmar Lindenberger (Institute of Energy Economics at the University of Cologne (EWI), 2012)
Renewable energies are meant to produce a large share of the future electricity demand. However, the availability of wind and solar power depends on local weather conditions and therefore weather characteristics must be considered when optimizing the future electricity mix. In this article we analyze the impact of the stochastic availability of wind and solar energy on the cost-minimal power plant mix and the related total system costs. To determine optimal conventional, renewable and storage capacities for different shares of renewables, we apply a stochastic investment and dispatch optimization model to the European electricity market. The model considers stochastic feed-in structures and full load hours of wind and solar technologies and different correlations between regions and technologies. Key findings include the overestimation of fluctuating renewables and underestimation of total system costs compared to deterministic investment and dispatch models. Furthermore, solar technologies are - relative to wind turbines - underestimated when neglecting negative correlations between wind speeds and solar radiation.
Keywords: C61; C63; Q40; 330; Stochastic programming; electricity; renewable energy