分散协调控制在风火混合电力系统中仿真研究

Simulation Study of Multiple Model Decentralized-coordinated Predictive Control for Hybrid Wind-thermal Power System

大规模风电接入电网对电力系统的运行和控制提出了更高的要求。提出了一种基于多模型预测控制的分散协调控制策略并应用于风火混合电力系统的仿真研究。该方法融合多模型预测控制和关联测量法的特点。为提高抗风机侧抗随机扰动的能力,一种增广相关测量法被用于混合电力系统的建模。基于贝叶斯概率的迭代方法用于计算各模型切换权值。一个简化的、具有代表性的风火混合电力系统模型用来验证该方法的控制效果,时域仿真和主导特征值分析说明了该方法的有效性。

The large-scale integration of wind power presents a higher requirement of power system operation and control. A multiple model predictive control based decentralized coordinated control, which combined the characteristics of multiple model predictive control(MPC) and interaction measurement modeling, was proposed and applied to the simulation study of a hybrid wind-thermal power system. In order to enhance the resistance against the stochastic disturbance from wind turbine, an augment correlative measured method was employed to hybrid power system modeling. The Bayesian probability based iteration method was employed to calculate the model weighting. A simple, generic hybrid power system model was used to demonstrate system performance contributions. Simulations of time response and dominated eigenvalue analysis illustrate the effectiveness of the proposed method.