Optimal Sizing of an Energy Storage Portfolio Considering Multiple Timescales

Energy storage is likely to play a key role in future power systems relying primarily on renewable generation. Appropriate sizing of these systems is vital for a reliable future power system. A variety of energy storage technologies exist, some of which are suited to store energy across different timescales than others. It is necessary to co-optimize all energy storage technologies to ensure that there is sufficient generation to utilise all devices. This requires considering both short and longer timescales simultaneously. This paper proposes a stochastic optimization algorithm for sizing of a portfolio of energy storage technologies that operate across a variety of timescales. Its application is demonstrated using a case study of the UK's transmission level demand, but with renewables scaled to meet the majority of energy demand.