Load Frequency Control Strategy of Interconnected Power System Based on Tube DMPC

Xinshan Wang
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Abstract

Solar thermal power generation shares technical characteristics with traditional thermal power generation. This enables rapid adjustment of turbine generator output to meet the demands of the power grid load for frequency modulation. However, fluctuations in light intensity lead to variations in interconnected power system parameters, posing challenges for load frequency control (LFC). In this study, we propose a Robust Distributed Model Predictive Control (RDMPC) method. This method achieves system trajectory tracking by solving the nominal system optimization problem. It also flexibly adjusts the weights of different Tube models to determine the optimal control law using the standard Tube online combination with various gain values. Additionally, we incorporate the states of adjacent areas into the feedback control law to achieve effective coordination between these areas. Using MATLAB/Simulink, we simulated the power system in two areas. Compared to standard Tube DMPC, our proposed algorithm effectively mitigates the impact of light intensity, enhances adjustment speed, reduces frequency fluctuation, and demonstrates superior control effectiveness.
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基于管式 DMPC 的互联电力系统负载频率控制策略
太阳能热发电与传统的火力发电具有相同的技术特点。这使得涡轮发电机的输出能够快速调整,以满足电网负载对频率调节的需求。然而,光照强度的波动会导致互联电力系统参数的变化,给负载频率控制(LFC)带来挑战。在本研究中,我们提出了一种鲁棒分布式模型预测控制(RDMPC)方法。该方法通过解决标称系统优化问题实现系统轨迹跟踪。它还能灵活调整不同管道模型的权重,利用标准管道在线组合与各种增益值来确定最优控制法则。此外,我们还将相邻区域的状态纳入反馈控制法,以实现这些区域之间的有效协调。我们使用 MATLAB/Simulink 模拟了两个区域的电力系统。与标准 Tube DMPC 相比,我们提出的算法能有效减轻光照强度的影响,提高调节速度,减少频率波动,并显示出卓越的控制效果。
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