论文部分内容阅读
大规模风力发电并网已经是新能源发展的必然趋势。利用储能装置平抑风力发电系统的输出功率已经成为风电系统不可或缺的一部分。由于风电功率的波动性大和随机性强等特点,传统的一阶低通滤波器控制策略具有一定的局限性,导致储能系统容量配置过高或利用率过低。本文将云模型控制策略引入风光储能系统中,利用一维云模型调整惯性滤波器的时间常数,进而实现风电功率的平滑控制,并与传统的定时间常数惯性滤波功率平滑方法进行了对比。仿真结果表明,在满足风电系统并网要求的前提下,基于云模型的平滑控制策略可以有效优化储能系统容量,降低了风储联合系统的成本。
Large-scale wind power grid integration is the inevitable trend of new energy development. The use of energy storage devices to stabilize wind turbine output power has become an integral part of wind power systems. The traditional first-order low-pass filter control strategy has some limitations due to the large fluctuation of wind power and strong randomness, which leads to the over capacity or under utilization of energy storage system. In this paper, the cloud model control strategy is introduced into the wind energy storage system. One-dimensional cloud model is used to adjust the time constant of the inertial filter, and then the wind power is smoothed and compared with the traditional time-constant inertia filtering power smoothing method. The simulation results show that the smoothing control strategy based on cloud model can effectively optimize the capacity of energy storage system and reduce the cost of wind power storage system, while meeting the grid connection requirements of wind power system.