Complicated ocean climatic conditions will affect the accuracy of wind power prediction for offshore wind farms, and energy storage can effectively compensate for wind power prediction errors. A method for energy storage capacity allocation of offshore wind farms considering the uncertainty of wind power forecast errors is proposed. First, a combined prediction model is used to predict the wind speed, obtaining the predicted value of wind power according to the relationship between wind power and wind speed, and comparing it with the actual measured value to obtain the wind power prediction error. Then, the goal is to minimize the sum of power cost and capacity cost of energy storage configuration. A robust chance constraint model that uses energy storage to compensate for the wind power prediction error to within the allowable interval is proposed, and the convex approximation and sampling average method are used to convert the model into a linear programming form to achieve an efficient solution. Finally, the impact of a typhoon event on the energy storage configuration of offshore wind farms is analyzed in the calculation example, and it is verified that the proposed model can effectively balance compensation effect and economy when dealing with the uncertainty of wind power forecast errors. The results can provide strong support for the large-scale deployment of energy storage in offshore wind farms in the future. This work is supported by the National Natural Science Foundation of China (No. 51977128).