Scheduling of energy storage

TL;DR

This paper explores optimal scheduling strategies for heterogeneous energy storage systems to minimize unserved energy in renewable energy grids, demonstrating policies that are effective even under uncertain future supply and demand conditions.

Contribution

It introduces a method for nearly optimal scheduling of diverse energy storage units, ensuring minimal imbalance in renewable energy systems with stochastic supply and demand.

Findings

Optimal policies are often independent of future supply-demand evolution.

Scheduling heterogeneous storage can significantly reduce unserved energy.

Policies remain effective under stochastic conditions.

Abstract

The increasing reliance on renewable energy generation means that storage may well play a much greater role in the balancing of future electricity systems. We show how heterogeneous stores, differing in capacity and rate constraints, may be optimally, or nearly optimally, scheduled to assist in such balancing, with the aim of minimising the total imbalance (unserved energy) over any given period of time. It further turns out that in many cases the optimal policies are such that the optimal decision at each point in time is independent of the future evolution of the supply-demand balance in the system, so that these policies remain optimal in a stochastic environment.