A hybrid energy storage array group control strategy for wind power smoothing

Tong Tong, Le Wei, Yuanye Chen, Fang Fang
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Abstract

With the increase of wind power generation, the safety and economy of power system operations are greatly influenced by the intermittency and fluctuation of wind power. To take the advantage of the complementary characteristics between different energy storage devices, a Hybrid Energy Storage System (HESS) consisting of Battery Energy Storage System (BESS) and Flywheel Energy Storage System (FESS) can alleviate the uncertainty of wind power. This article has proposed a coordinated control strategy through group consensus algorithm based on Model Predictive Control (MPC) for Hybrid Energy Storage Array (HESA) to smooth wind power fluctuations. To allocate power commands to the FESS and BESS, the fluctuation of wind power output is extracted with different frequency domain characteristics as instructions by Empirical Mode Decomposition (EMD) technology. Moreover, a group consensus algorithm based on MPC is proposed to complete the adaptive power allocation of energy storage units. Eventually, the actual wind farm data is used for the simulation to verify the effect of control strategy proposed in this paper. It can be seen that the developed group consensus algorithm based on MPC can cope with different frequency power commands, avoid overcharging and discharging of energy storage media, and smooth wind power effectively.
用于风电平滑的混合储能阵列群控制策略
随着风力发电量的增加,电力系统运行的安全性和经济性受到风力发电间歇性和波动性的极大影响。为了利用不同储能设备之间的互补性,由电池储能系统(BESS)和飞轮储能系统(FESS)组成的混合储能系统(HESS)可以缓解风力发电的不确定性。本文提出了一种基于模型预测控制(MPC)的混合储能阵列(HESA)群组共识算法协调控制策略,以平滑风电波动。为了将功率指令分配给 FESS 和 BESS,利用经验模式分解(EMD)技术提取了具有不同频域特征的风电输出波动。此外,还提出了一种基于 MPC 的群体共识算法,以完成储能单元的自适应功率分配。最后,利用实际风电场数据进行仿真,验证本文提出的控制策略的效果。可以看出,所开发的基于 MPC 的群组共识算法能够应对不同频率的功率指令,避免储能介质的过充和过放,并有效平滑风功率。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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