Wind power has been proven to have the ability to participate in the frequency modulation (FM) market. Using batteries to improve wind power stability can better aid wind farms participating in the FM market. Battery energy storage system (BESS) has a promising future in applying regulation and load management in the power grid. For regulation services

normally

the regulation power prediction is estimated based on the required maximum regulation capacity; the power needed for the specific regulation service is unknown to the BESS owner. However

this information is needed in the regulation model when formulating the linearised BESS model with a constraint on the state of charge (SoC). This compromises the accuracy of the model greatly when it is applied for regulation service. Moreover

different control strategies can be employed by BESS. However

the current depth of discharge (DoD) based models have difficulties in being used in a linearization problem. Due to the consideration of the control strategy

the model becomes highly nonlinear and cannot be solved. In this paper

a charging rate (C-rate) based model is introduced

which can consider different control strategies of a BESS for cooperation with wind farms to participate in wind farm estimation error compensation

load management

energy bid

and regulation bid. First

the limitation of conventional BESS models are listed

and a new C-rate-based model is introduced. Then the C-rate-based BESS model is adopted in a wind farm and BESS cooperation scheme. Finally

experimental studies are carried out

and the DoD model and C-rate model optimization results are compared to prove the rationality of the C-rate model.