A MILP model for optimising multi-service portfolios of distributed energy storage

Abstract

Energy storage has the potential to provide multiple services to several sectors in electricity industry and thus support activities related to generation, network and system operation. Hence aggregating the value delivered by storage to these sectors is paramount for promoting its efficient deployment in the near future, which will provide the level of flexibility needed to deal with the envisaged high renewables share and the increase in peak demand driven by transport and heating electrification. In this context, we develop a Mixed Integer Linear Programming (MILP) model to schedule operation of distributed storage by coordinating provision of a range of system services which are rewarded at different market prices. The model maximises distributed storage's net profit while providing distribution network congestion management, energy price arbitrage and various reserve and frequency regulation services through both active and reactive power control. We demonstrate benefits associated with the coordination of these services and its impacts on commercial strategies to determine optimal multi-service portfolios in the long term. We also demonstrate the value of reactive power control to support not only distribution network congestion management, but also efficient trading of energy and balancing services which are usually treated through active power-only control.In addition, we use the model to price the service of distribution network congestion management and propose an efficient investment policy to upgrade distribution network capacity in the presence of distributed storage. Finally, several case studies under current market conditions in Great Britain (GB) demonstrate that distributed storage revenues associated with frequency control services are significantly more profitable.

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