  This paper considers the representation of energy storage in electricity
sector capacity planning models. The incorporation of storage in long-term
systems models of this type is increasingly relevant as the cost of storage
technologies, particularly batteries, and of complementary variable renewable
technologies, decline. To value storage technologies appropriately, a
representation of linkages between time periods is required, breaking classical
temporal aggregation strategies that greatly improve computation time. We
appraise approaches to address this problem, highlighting a common underlying
structure, conditions for lossless aggregation, and challenges of aggregation
at relevant geographical scales. We then investigate solutions to the modeling
problem including a decomposition scheme to avoid temporal aggregation at a
parallelizable computational cost. These examples frame aspects of the problem
ripe for contributions from the operational research community.
