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Model Predictive Control for Load Frequency Control with Wind Turbines

机译:风力发电机负荷频率控制的模型预测控制

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摘要

Reliable load frequency (LFC) control is crucial to the operation and design of modern electric power systems. Considering the LFC problem of a four-area interconnected power system with wind turbines, this paper presents a distributed model predictive control (DMPC) based on coordination scheme. The proposed algorithm solves a series of local optimization problems to minimize a performance objective for each control area. The scheme incorporates the two critical nonlinear constraints, for example, the generation rate constraint (GRC) and the valve limit, into convex optimization problems. Furthermore, the algorithm reduces the impact on the randomness and intermittence of wind turbine effectively. A performance comparison between the proposed controller with and that without the participation of the wind turbines is carried out. Good performance is obtained in the presence of power system nonlinearities due to the governors and turbines constraints and load change disturbances.
机译:可靠的负载频率(LFC)控制对于现代电力系统的运行和设计至关重要。考虑到四区域风电机组的LFC问题,本文提出了一种基于协调方案的分布式模型预测控制(DMPC)。所提出的算法解决了一系列局部优化问题,以最小化每个控制区域的性能目标。该方案将两个关键的非线性约束(例如发电率约束(GRC)和阀门极限)纳入凸优化问题。此外,该算法有效地减小了对风力涡轮机的随机性和间歇性的影响。在有和没有风力涡轮机参与的情况下,对所提出的控制器进行了性能比较。由于调速器和涡轮机的限制以及负载变化的干扰,在电力系统存在非线性的情况下可以获得良好的性能。

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  • 来源
    《Journal of control science and engineering》 |2015年第2015期|282740.1-282740.17|共17页
  • 作者单位

    Department of Electrical Engineering, North China University of Science and Technology, Tangshan 063000, China,The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;

    The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;

    The State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources, North China Electric Power University, Beijing 102206, China;

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