Crown scheduling is a static scheduling approach for sets of parallelizable tasks with a common deadline, aiming to minimize energy consumption on parallel processors with frequency scaling. We demonstrate that crown schedules are robust, i.e. that the runtime prolongation of one task by a moderate percentage does not cause a deadline transgression by the same fraction. In addition, by speeding up some tasks scheduled after the prolonged task, the deadline can still be met at a moderate additional energy consumption. We present a heuristic to perform this re-scaling online. We evaluate our approach with scheduling experiments on synthetic task sets.