The coordinated control of wind power and battery energy storage system(BESS)needs to deal with multiple inconsistent sub-objectives. The sub-objectives are weighted by weighting factors

which will greatly influence the control effects. Firstly

it is verified by simulations that

constant weighting factors-based multi-objective optimization control cannot adapt the random nature of wind power. Secondly

a dynamic weighting method is proposed

which is based on gridding searching of the optimal weighting factors. In order to determine the optimal weighting factors

an evaluation method by using the membership function and entropy weight method is proposed. It is shown by simulation studies that the proposed method has significant effects on the output power and state of charge(SOC)control of BESS while smoothing wind power

thus adaptively adjusting the weighting factor of each objective according to the wind power fluctuations

the SOC and the charge/discharge power of BESS. This work is supported by National Key Technologies R&D Program(No. 2013BAA01B04)and State Grid Corporation of China(No. 520940140021).