A multiperiodal management method at user level for storage systems using artificial neural network forecasts

The increase of renewable non-programmable production and the necessity to locally self-consume the produced energy led to utilize ever more storage systems. To correctly utilize storage systems, an opportune management method has to be utilized. This paper implements a multi-period management method for storage systems, using different management strategies. The method aims to minimize the total absorbed and supplied energy or the peak power exchanged with the grid. The results show the effectiveness of the method in diminishing the energy exchanged with the grid and also the possibility to optimize the performance of the storage systems.