• Energy Research

Abstract Future “net-zero” electricity systems in which all or most generation is renewable may require very high volumes of storage in order to manage the associated variability in the generation-demand balance. The physical and economic characteristics of storage technologies are such that a mixture of technologies is likely to be required. This poses nontrivial problems in storage dimensioning and in real-time management. We develop the mathematics of optimal scheduling for system adequacy, and show that, to a good approximation, the problem to be solved at each successive point in time reduces to a linear programme with a particularly simple solution. We argue that approximately optimal scheduling may be achieved without the need for a running forecast of the future generation-demand balance. We consider an extended application to GB storage needs, where savings of tens of billions of pounds may be achieved, relative to the use of a single technology, and explain why similar savings may be expected elsewhere.

Abstract Future “net-zero” electricity systems in which all or most generation is renewable may require very high volumes of storage in order to manage the associated variability in the generation-demand balance. The physical and economic characteristics of storage technologies are such that a mixture of technologies is likely to be required. This poses nontrivial problems in storage dimensioning and in real-time management. We develop the mathematics of optimal scheduling for system adequacy, and show that, to a good approximation, the problem to be solved at each successive point in time reduces to a linear programme with a particularly simple solution. We argue that approximately optimal scheduling may be achieved without the need for a running forecast of the future generation-demand balance. We consider an extended application to GB storage needs, where savings of tens of billions of pounds may be achieved, relative to the use of a single technology, and explain why similar savings may be expected elsewhere.

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 minimizing 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.This article is part of the theme issue ‘The mathematics of energy systems’.

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 minimizing 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.This article is part of the theme issue ‘The mathematics of energy systems’.