Decentralized Model-Predictive Control of a Coupled Wind Turbine and Diesel Engine Generator System
Decentralized Model-Predictive Control of a Coupled Wind Turbine and Diesel Engine Generator System
复制标题
风力发电机组和柴油机发电机耦合系统的分散模型预测控制
作者：
Milad Shojaee;Fatemeh Mohammadi Shakiba;S. Azizi
可再生能源发电机组提供持续和高质量的电力至关重要。这种要求在独立的风力-柴油系统中甚至更加明显，其中风力并不总是恒定或可用的。此外，期望以从柴油发动机消耗较少燃料的方式使提取的功率最大化。本文提出了一种新的方法来设计分散模型预测控制器来控制一个独立的发电系统的频率和功率，该发电系统由一个风力涡轮机子系统机械耦合柴油机发电机子系统。设计了两个分散的模型预测控制器来调节频率和有功功率，同时考虑了两个子系统之间的机械耦合，两个控制器之间不存在通信链路。仿真结果表明，所提出的分散控制器优于基准分散线性二次高斯（LQG）控制器在消除干扰风和负载功率的变化。此外，它表明，所提出的控制策略对系统的所有参数的并发变化相比，LQG控制器具有可接受的鲁棒性能。
It is highly critical that renewable energy-based power generation units provide continuous and high-quality electricity. This requirement is even more pronounced in standalone wind–diesel systems where the wind power is not always constant or available. Moreover, it is desired that the extracted power be maximized in such a way that less fuel is consumed from the diesel engine. This paper proposes a novel method to design decentralized model-predictive controllers to control the frequency and power of a single standalone generation system, which consists of a wind turbine subsystem mechanically coupled with a diesel engine generator subsystem. Two decentralized model-predictive controllers are designed to regulate the frequency and active power, while the mechanical coupling between the two subsystems is considered, and no communication links exist between the two controllers. Simulation results show that the proposed decentralized controllers outperform the benchmark decentralized linear-quadratic Gaussian (LQG) controllers in terms of eliminating the disturbances from the wind and load power changes. Furthermore, it is demonstrated that the proposed control strategy has an acceptable robust performance against the concurrent variations in all parameters of the system as compared to the LQG controllers.