Power-intensive industry plays a key role in balancing supply and demand in the energy grid: by offering flexible power, industry can reduce operating costs and grid operators can avoid technical failures. Recently, research has started to try and address the challenging question of determining the amount of power curtailment (i.e., how much power can be reduced for how long) without violating any process constraints. We consider several machine learning methods to assess the curtailment potential in a coldstore, based on historical data.