计及碳收益的风电场混合储能容量优化配置

风电场输出功率波动剧烈，直接并网会影响电力系统的安全稳定运行，需要配置储能平滑风电功率使其满足并网要求。为克服滑动平均法追随性差而导致储能配置容量较大的问题，提出分级滑动平均法用于确定风电功率平滑目标；采用Butterworth低通滤波对风电功率偏移量进行分解，将低频分量和高频分量分别作为锂电池储能和飞轮储能的参考功率；考虑储能初始投资及置换等成本以及售电收益、碳交易收益，建立风电场混合储能容量优化配置模型，并采用自适应混沌粒子群优化算法进行求解；利用某48MW风电场的运行数据进行仿真验证。仿真结果表明：分级滑动平均法更适用于确定风电功率平滑目标，锂电池与飞轮混合储能有利于提高风储系统全生命周期的净收益。

Optimal Configuration of Hybrid Energy Storage Capacity for Wind Farms Considering Carbon Trading Revenue

The output power of wind farms fluctuates strongly, and direct grid connection will affect the safe and stable operation of the power system. Therefore, it is necessary to optimize energy storage configuration to smooth the wind power, so as to meet the requirements of grid connection. In order to deal with the large energy storage capacity caused by poor tracking of the moving average method, a hierarchical moving average method was proposed to determine the target in smoothing wind power. The wind power offset was decomposed by a Butterworth low-pass filter, and the low-frequency and high-frequency components were used as the reference power of lithium battery energy storage and flywheel energy storage, respectively. In view of the cost of initial investment and replacement of energy storage as well as the revenue from electricity sales and carbon trading, an optimal configuration model of hybrid energy storage capacity for wind farms was established and solved by an adaptive chaotic particle swarm optimization algorithm. Simulation and verification were carried out according to the operation data of a 48MW wind farm. The simulation results show that the hierarchical moving average method is more suitable for determining the target in smoothing wind power, and the hybrid energy storage of lithium battery and flywheel can improve the net income of the energy storage system of wind farms in the whole life cycle.