基于模型预测控制的混合电力系统快速频率响应

Abhishek Varshney, Renuka Loka, A. M. Parimi
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引用次数: 1

摘要

可再生能源(RESs)在混合电力系统(hps)中的大规模渗透主要由异步接口源组成。通过使用电力电子转换器(PECs)实现RESs的异步互连;然而,它随后减少了系统的惯性,由于较少的旋转质量。系统惯性的减小导致了较高的频率变化率(RoCoF)。因此,高RoCoF的频率控制变得具有挑战性。为了将频率维持在标称值,负载和发电之间的功率平衡是必要的。可再生能源的电力过剩或亏缺是不确定的,随机负荷扰动应与发电和储存的变化相匹配。由于高RoCoF,系统维持功率平衡的响应应在最短时间内获得。因此,利用可用储量进行快速频率响应(FFR)是至关重要的。本文提出了一种改进的模型预测控制(MPC),通过在目标函数中引入RoCoF来实现混合动力系统(HPS)中主要使用燃料电池(FC)存储的FFR问题。通过MATLAB/Simulink对恒步长和随机负载波动和风扰动两种情况下的动态模型进行测试,比较了改进后的MPC控制器与传统PID控制器和MPC控制器的性能。各种情况下的仿真结果表明,所提出的MPC改善了阶跃响应的性能参数(沉降时间、峰值超调量和峰值幅值)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fast Frequency Response Using Model Predictive Control for A Hybrid Power System
Large-scale penetration of Renewable Energy Sources (RESs) in Hybrid Power Systems (HPSs) consists of predominantly asynchronously interfaced sources. Asynchronous interconnection of RESs is made possible by using Power Electronic Converters (PECs); however, it subsequently reduces the system inertia due to less rotational mass. The decrease in system inertia causes a high Rate of Change of Frequency (RoCoF). Consequently, frequency control becomes challenging with high RoCoF. To maintain the frequency at a nominal value, the power balance between the load and generation is necessary. The excess or deficit in power from RES is uncertain, and stochastic load disturbances should match generation and storage changes. Owing to high RoCoF, the response of the system to maintain power balance should be obtained within a minimum time. Therefore, Fast Frequency Response (FFR) using the available reserves is of prime significance. This paper addresses the FFR problem by proposing a modified Model Predictive Control (MPC) by introducing RoCoF in the objective function to achieve FFR using primarily Fuel Cell (FC) storage in a Hybrid Power System (HPS). The modified MPC controller's performance is compared with the conventional PID and MPC controllers by testing the dynamic model for both situations - i) constant step and ii) random load fluctuations and wind disturbances using MATLAB/Simulink. Simulation results under various cases show that the proposed MPC has improved the performance parameters (settling time, peak overshoot, and peak-peak magnitude) of the step response.
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