Contingency Reserve Evaluation for Fast Frequency Response of Multiple Battery Energy Storage Systems in a Large-scale Power Grid

Recently,the fast frequency response(FFR)service by large-scale battery energy storage systems(BESSs)has been successfully proved to arrest the frequency excursion during an unexpected power outage.However,adequate frequency response relies on proper evaluation of the contingency reserve of BESSs.The BESS FFR reserve is commonly managed under fixed contracts,ignoring various response characteristics of different BESSs and their coexisting interactions.This paper proposes a new methodology based on dynamic grid response and various BESS response characteristics to optimise the FFR reserves and prevent the frequency from breaching the under-frequency load shedding(UFLS)thresholds.The superiority of the proposed method is demonstrated to manage three large-scale BESSs operating simultaneously in an Australian power grid under high renewable penetration scenarios.Further,the proposed method can identify remaining battery power and energy reserve to be safely utilised for other grid services(e.g.,energy arbitrage).The results can provide valuable insights for integrating FFR into conventional ancillary services and techno-effective management of multiple BESSs.

A quasi-automated generation control strategy for multiple energy storage systems to optimize low-carbon benefits

Integrating a battery energy storage system(ESS)with a large wind farm can smooth the intermittent power obtained from the wind farm,but the smoothing function will not be achieved if multiple ESSs are used to smooth the fluctuations in individual wind power plants in a distributed pattern.Therefore,this study focuses on the development of a control strategy to optimize the use of multiple ESSs to accelerate the adoption of wind energy resources.This paper proposes a quasi-automated generation control(QAGC)strategy to coordinate multiple ESSs,which responds to the grid dispatch demand rather than smoothing out the intermittent power from individual wind farms.The aims of QAGC are to ensure that multiple ESSs provide a service that is as balanced as possible,so more wind power systems at various scales can be accepted by the grid,as well maximizing the low-carbon benefits of ESSs.The effectiveness of QAGC is demonstrated by using data from an actual gigawatt scale cluster of wind plants.