Abstract
The rapid development and growth of battery storage have heightened an interest in the co-location of battery energy storage systems (BESS) with renewable energy projects which enables the stacking of multiple revenue streams while reducing connection charges of BESS. To help wind energy industries better understand the coordinated operation of BESS and wind farms and its associated profits, this paper develops a simulation model to implement a number of coordination strategies where the BESS supplies enhanced frequency response (EFR) service and enables the time shift of wind generation based on the UK perspective. The proposed model also simulates the degradation of Lithium-Ion battery and incorporates a state of charge (SOC) dependent limit on the charge rate derived from a constant current-constant voltage charging profile. In addition, a particle swarm optimisation-based battery sizing algorithm is developed here on the basis of the simulation model to determine the optimal size of the co-located BESS along with SOC-related strategy variables that maximise the net present value of the wind + BESS system at the end of the EFR contract.
Highlights
Battery energy storage systems (BESS) play an important role in the transition to a low-carbon electricity generation, offering great potential for improving the system flexibility and facilitating the integration of renewables [1]
This paper proposes a UK-based modelling framework to optimise the size of a BESS
If SOCt is above SOCld, the surplus energy of BESS is allowed to transfer to WF meter (WFm) and sell ) subject to the available ampacity of connection point, the sold as wind energy
Summary
Battery energy storage systems (BESS) play an important role in the transition to a low-carbon electricity generation, offering great potential for improving the system flexibility and facilitating the integration of renewables [1]. This paper proposes a UK-based modelling framework to optimise the size of a BESS co-located with an existing wind farm under different coordination strategies where the BESS is used to provide EFR service and capture the wind generation which would otherwise be curtailed due to the limited ampacity of their common connection point. The paper is structured as follows: Section 2 describes the simulation model of a wind + BESS system, including coordination strategies along with the degradation model and operational limits of the BESS; Section 3 introduces revenues and expenses of the wind + BESS system and the PSO-based sizing algorithm; Section 4 assesses optimisation results and profitability of the co-located system under each strategy; Section 5 presents conclusions and recommendations for further work
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