In steel coil storages, gantry cranes store steel coils in a triangular stacking pattern and retrieve them to serve customer demand on time. The crane movements cause high energy consumption depending on the weight of the steel coils and the direction of the crane movement, which provides a starting point for more efficient crane operation in terms of energy consumption. However, current literature on crane scheduling in steel coil storages and neighboring domains mainly focuses on time-oriented objectives and neglects energy consumption. Therefore, we justify the problem of energy-oriented crane scheduling in steel coil storages and develop a mixed-integer linear programming model and a simulated annealing algorithm. The methods aim to minimize the energy consumed by crane movements while serving customer demand. We present extensive computational experiments comparing the energy-oriented approach against two popular alternatives from the literature. The energy consumption of crane movements can be reduced by 2–22% using energy-oriented crane scheduling compared to the alternatives with an identical customer service level. The simulated annealing algorithm solves instances of the size commonly found in the industrial practice of steel coil storage within an amount of time suitable for practical applications. Since extensive test instances for crane scheduling of steel coil storages have not been available thus far, we make our test instances accessible as a starting point for future research efforts.