基于经验模式分解的风电场多时间尺度复合储能控制策略

A Multi-Time Scale Control Strategy of Hybrid Energy Storage System in Wind Farm Based on Empirical Mode Decomposition

储能装置在平滑风电功率波动、提升电能质量等方面具有重要的作用。目前常见的蓄电池、超级电容复合储能系统受制于成本因素而普遍容量较小,难以破解风电并网瓶颈。为此提出了一种由压缩空气、蓄电池与超级电容组成的多元复合储能系统,利用压缩空气储能容量大、成本低的优势,对风电功率"削峰填谷",有效提高电网消纳风电的能力。针对多元复合储能系统中多种储能装置的协调控制这一难题,在分析风能波动幅频特性基础上,提出了一种基于经验模式分解原理的多时间尺度复合储能功率协调控制策略,将风电场输出功率分解为多个不同波动时间尺度的子分量,根据各储能装置响应特性和储能成本重构子分量,生成对应目标功率,实现能量在不同储能装置间的优化分配。仿真算例验证了所提复合储能结构和控制策略的有效性。

Energy storage devices play important role in smoothing wing power output fluctuation and improving power quality. Due to the cost factor, the capacity of current common hybrid energy storage system composed of batteries with supercapacitors is not large enough in general, so that it is hard to cope with the bottleneck of grid-connection of wind farms by such an energy storage system. For this reason, a multi-component energy storage system composed of compressed air, batteries and superconductors is proposed, and utilizing the superiority in high energy storage capacity and low cost of compressed air the proposed multi-component energy storage system can be utilized in the peak load shaving and effectively enhances the wind power accommodation ability of power grid. In allusion to the coordinated control of various kinds of energy storage devices in a multi-component energy storage system, on the basis of analyzing the amplitude-frequency characteristic of wind energy fluctuation a multi-time scale coordinated control strategy for hybrid energy storage system based on the principle of empirical mode decomposition is put forward, in which the wind power output is decomposed into sub-components in different fluctuating time-scales and the sub-components are reconstructed in accordance with the response characteristics and the energy storage costs of energy storage devices to generate correspond objective power to achieve the optimal energy allocation among various energy storage devices. The effectiveness of the structure of the proposed hybrid energy storage system and that of the control strategy are validated by simulation examples.