Abstract
As variable renewable energy (VRE) plants such as wind and solar power start to play a major role in many electric power systems around the world, strategies for dealing with the additional variability introduced into the grid by such plants are becoming more important. Energy storage systems (EES), generally based on batteries, are now often required by grid operators in order to smooth out short-term fluctuations from wind and solar generation. However, sizing procedures are often based on heuristic considerations, rather than being grounded in a rigorous mathematical framework. In the current work, analytical formulae for the required minimal capacity of energy storage systems for smoothing applications, based on methods from probability theory, have been derived and validated against simulations. The methodology combines rigorous derivations of the required storage capacity for ramp mitigation with a curve-fitting approach based on Monte Carlo simulations for the estimation of the additional capacity required for state-of-charge control. All results have been obtained for generalized Laplace distributions, which are known to be a good fit to output power variations of VRE plants. The results are believed to contribute to a more profound understanding of the processes determining the required EES capacity for VRE power smoothing.
Published Version
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