基于迭代辨识方法的含风电多干扰电力系统阻尼控制

风电接入电力系统后的低频振荡控制是保证电网稳定运行的关键。随着风电场联网规模的不断扩大,当风电接入由于电网结构、负荷潮流、发电机励磁控制等因素导致的阻尼不足形成的多干扰环境下电力系统后,模型辨识误差因素给电力系统的辨识与阻尼控制带来了很大的难题,常常会恶化阻尼控制效果。针对此问题,首先以风电功率波动信号作为辨识信号,建立风电接入多干扰环境下电力系统闭环模型;然后基于递推最小二乘法和Vinnicombe距离理论,提出一种迭代辨识方法,并给出方法实现的整个步骤,该方法充分考虑辨识误差因素,可以实时辨识出电力系统最优电力系统模型和最优阻尼控制器模型;最后,以风电接入四机两区域间降阶模型为例,采用提出的方法进行仿真,并与传统迭代辨识方法进行了对比。仿真结果表明,所提方法可以有效抑制风电接入下多干扰电力系统的低频振荡,实现稳定的阻尼控制。

Damping Control of Power System Containing Wind Power in Multi-interference Environment Based on Iterative Identification Method

The low frequency oscillation control of wind power integration is the key to ensure the stable operation of power system. With the steady expansion of network scale of wind farms, the power system in a multi-interference environment is formed for lack of damping due to the grid structure, load flow, generator excitation control and other factors. When the wind power is integrated, the error factor of model identification will bring about problems to the identification and damping control of the power system. It often deteriorates the effect of damping control. For this problem, firstly, the wind power fluctuation signal is used as an identification signal, and a power system closed-loop model in multi-interference environment involving the wind power integration is built. Secondly, an iterative identification method based on the recursive least square method and Vinnicombe distance is proposed and the whole implementation steps are given. In this method, the optimal power system model and optimal damping controller model can be identified online by fully considering the identification error factors. Finally, taking one four-machine two-area wind power access system model as an example, the simulations are carried out by using the proposed method and compared with the traditional iterative identification method. Simulation results show the correctness and effectiveness of the proposed method, which can effectively suppress the low frequency oscillation under the multi-interference of power system with wind power integration, while achieving stable damping control.