变速风力发电机组的经济模型预测控制  

Economic Model Predictive Control of Variable-speed Wind Energy Conversation Systems

作　　者：崔靖涵 刘向杰[1] CUI Jing-han;LIU Xiang-jie(The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources,North China Electric PowerUniversity,Beijing 102206,China)

机构地区：[1]华北电力大学新能源电力系统国家重点实验室,北京102206

出　　处：《控制工程》2019年第3期431-439,共9页Control Engineering of China

基　　金：国家自然科学基金(61673171;61603134;61533013);中央高校基本科研业务费专项资金项目(2017XS065)

摘　　要：在风力发电控制系统中,模型预测控制是降低发电成本、提高能源利用率的有效方式。经济模型预测控制,旨在用一个优化问题实现不同区域控制目标,同时实现运行区域间的高效切换。以5 MW风电机组作为研究对象,对两种控制策略进行了仿真对比。结果表明经济模型预测控制不仅实现机组不同区域的控制目标同时提高闭环经济性能,尤其在区域切换过程中,可以有效提高风能利用,减小结构疲劳,对改善风电的电能质量,延长机组使用寿命具有重要意义。For the wind energy conversation system(WECS), model predictive control(MPC) has become an effective way to reduce the cost of generating electricity and improve the utilization of energy. This paper presents a new control strategy, economic model predictive control(EMPC), to achieve control objectives of WECS with one on-line optimization problem, while realizing efficient switching between two operation regions. The simulation research of the 5 MW WECS has been carried out aiming to compare the classical MPC and EMPC. The simulation results show that the EMPC can achieve the objectives while improving wind energy capture and reducing the fatigue load, especially in the switching process which has great significance on the improvement of the power quality and prolonging the service life of the facilities.

关 键 词：风力发电机组 经济模型预测控制 经济性能 风能利用 疲劳负荷 

分 类 号：TP18[自动化与计算机技术—控制理论与控制工程]