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The control of multiple battery energy storage systems (BESSs) to provide frequency response will be a challenge in future smart grids. This paper proposes a hierarchical control of BESSs with two decision layers: the aggregator layer and the BESS control layer. The aggregator layer receives the states of charge (SoC) of BESSs and sends a command signal to enable/disable the BESS control layer. The BESS controller was developed to enable the BESSs to respond from the highest to lowest SoC when the frequency drops, and from lowest to highest when it rises. Hence, the BESS’s response is prioritised to reduce the impact on the power system and end-users during the service. The BESS controller works independently when a failure occurs in the communication with the aggregator. The dynamic behaviour of the population of the controllable BESSs was modelled based on a Markov chain. The model demonstrates the value of aggregation of BESSs for providing frequency response and evaluates the effective capacity of the service. The model was demonstrated on the 14-machine South-East Australian power system with a 14.5 GW load. 254 MW of responsive capacity of aggregated batteries was effective in reducing the system frequency deviation below 0.2 Hz following a sequence of disturbances.

The role of ancillary services related to the frequency control have become increasingly important in the smart grids. Demand Side Response is a competitive resource that can be used to regulate the grid frequency. This paper describes the use of heat pumps and fridges to provide ancillary services of frequency response so that to continuously balance the supply with demand. The power consumption of domestic units is usually small and, therefore, the aggregation of large numbers of small units should be able to provide sufficient capacity for frequency response. In this research, dynamic frequency control was developed to evaluate the capacity that can be gathered from the aggregation of domestic heat pumps and fridges for frequency response. The potential of frequency response was estimated at a particular time during winter and summer days. We also investigated the relationship between both loads (domestic heat pumps and fridges) to provide Firm Frequency Response service. A case study on the simplified Great Britain power system model was developed. Based on this case study, three scenarios of load combination were simulated according to the availability of the load and considering cost savings. It was demonstrated that the aggregation of heat pumps and fridges offered large power capacity and, therefore, an instantaneous frequency response service was achievable. Finally, the economic benefit of using an aggregated load for Firm Frequency Response service was estimated.