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Two‐stage optimal scheduling for aggregators of batteries owned by commercial consumers

This study proposes a two-stage optimisation technique to schedule batteries owned by commercial consumers through an aggregator. This approach captures energy arbitrage and peak shaving benefits at the consumer level, as well as frequency regulation benefit at the system level. The day-ahead stage optimisation maximises the expected profits, considering the battery degradation cost as well as the uncertainties on customer demand profiles and frequency regulation prices. It determines the regulation capacity that the aggregator can bid at each hour, as well as the consumers’ peak demand targets and battery state-of-charge (SoC) target trajectories. The near real-time stage involves two steps: a rule-based pre-process and a snapshot optimisation. It dispatches the batteries to follow the aggregator regulation capacity bids, to track the SoC target trajectories and to ensure that the peak demand targets are not violated. A case study demonstrates that the proposed two-stage approach effectively dispatches batteries to achieve both consumer and system-level benefits.