Determination of characteristic parameters of battery energy storage system for wind farm

Abstract

Integrating a battery energy storage system (BESS) with a wind farm can smooth power fluctuations from the wind farm. Battery storage capacity (C), maximum charge/discharge power of battery (P) and smoothing time constant (T) for the control system are three most important parameters that influence the level of smoothing (LOS) of output power transmitted to the grid. The economic cost (EC) of a BESS should also be taken into consideration when determining the characteristic parameters of BESS (C, P). In this study, an artificial neural network-based long-term model of evaluated BESS technical performance and EC is established to reflect the relationship between the three parameters (C, P, T) and LOS of output power transmitted to the grid, the EC of BESS. After that, genetic algorithm is used to find optimal parameter combination of C, P and T by optimising the objective function derived from the mathematical model constructed. The simulation results of the example indicate that the parameter combination of C, P and T obtained by the proposed method can better not only meet the technical demand but also achieve maximum economic profit.