  The increase in renewable energy sources (RESs), like wind or solar power,
results in growinguncertainty also in transmission grids. This affects grid
stability through fluctuating energy supplyand an increased probability of
overloaded lines. One key strategy to cope with this uncertainty isthe use of
distributed energy storage systems (ESSs). In order to securely operate power
systemscontaining renewables and use storage, optimization models are needed
that both handle uncertaintyand apply ESSs. This paper introduces a compact
dynamic stochastic chance-constrained DC optimalpower flow (CC-OPF) model, that
minimizes generation costs and includes distributed ESSs. AssumingGaussian
uncertainty, we use affine policies to obtain a tractable, analytically exact
reformulation asa second-order cone problem (SOCP). We test the new model on
five different IEEE networks withvarying sizes of 5, 39, 57, 118 and 300 nodes
and include complexity analysis. The results showthat the model is
computationally efficient and robust with respect to constraint violation risk.
Thedistributed energy storage system leads to more stable operation with
flattened generation profiles.Storage absorbed RES uncertainty, and reduced
generation cost.
