Storage Management in Modern Electricity Power Grids
For researchers and engineers in smart grid management, this offers a simple probabilistic tool for storage control, though it is an incremental contribution.
The paper proposes a stochastic method to model energy storage levels in electricity grids, enabling prediction of surplus or deficit events. The approach provides a probabilistic framework for storage management.
This letter introduces a method to manage energy storage in electricity grids. Starting from the stochastic characterization of electricity generation and demand, we propose an equation that relates the storage level for every time-step as a function of its previous state and the realized surplus/deficit of electricity. Therefrom, we can obtain the probability that, in the next time-step: (i) there is a generation surplus that cannot be stored, or (ii) there is a demand need that cannot be supplied by the available storage. We expect this simple procedure can be used as the basis of electricity self-management algorithms in micro-level (e.g. individual households) or in meso-level (e.g. groups of houses).