qZSI-VSG 并网风力发电系统的无约束优化 MPC 方法

IF 5 2区 工程技术 Q1 ENGINEERING, ELECTRICAL & ELECTRONIC
Yang Zhang , Sicheng Li , Yihan Liu , Zhongjian Tang , Bing Luo
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引用次数: 0

摘要

随着风力发电的日益普及,传统的逆变器控制方法可能会因惯性减小和易受参数变化的影响而导致电网不稳定。为了解决这一问题,虚拟同步发电(VSG)技术与具有内置升压功能的准 Z 源逆变器(qZSI)相结合。首先,引入了有限开关序列控制策略和无约束优化模型预测控制(MPC)策略,以实现 qZSI-VSG 系统的多目标优化控制。降低了逆变器的平均开关频率,增强了系统减缓风机输出波动的能力,并将电流谐波降至最低。此外,由于无需将权重系数直接添加到成本函数中,该算法的计算复杂度也得到了简化。最后,理论分析和实验结果验证了所提控制策略的正确性和有效性。总之,这种方法为应对风力发电日益融入电网所带来的挑战提供了一种前景广阔的解决方案。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Unconstrained optimization MPC method for qZSI-VSG grid-connected wind power system
As the wind power generation becomes increasingly popular, the conventional inverter control methods may lead to power grid instability due to the reduction of inertia and susceptibility to parameter variations. In order to address this problem, a virtual synchronous generation (VSG) technology is combined with the quasi Z-source inverter (qZSI), which has the built-in boost function. To begin with, a finite switch sequence control strategy and an unconstrained optimization model predictive control (MPC) strategy are introduced to achieve multi-objective optimal control of the qZSI-VSG system. The average switching frequency of the inverter is reduced, the ability of the system to mitigate fluctuations in wind turbine output is enhanced, and the current harmonics are minimized. In addition, the computational complexity of the algorithm is simplified by eliminating the need for weight coefficients to be directly added to the cost function. Finally, the correctness and effectiveness of the proposed control strategy are verified by theoretical analysis and experimental results. Overall, this approach offers a promising solution to the challenges posed by the increasing integration of wind power into the power grid.
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来源期刊
International Journal of Electrical Power & Energy Systems
International Journal of Electrical Power & Energy Systems 工程技术-工程:电子与电气
CiteScore
12.10
自引率
17.30%
发文量
1022
审稿时长
51 days
期刊介绍: The journal covers theoretical developments in electrical power and energy systems and their applications. The coverage embraces: generation and network planning; reliability; long and short term operation; expert systems; neural networks; object oriented systems; system control centres; database and information systems; stock and parameter estimation; system security and adequacy; network theory, modelling and computation; small and large system dynamics; dynamic model identification; on-line control including load and switching control; protection; distribution systems; energy economics; impact of non-conventional systems; and man-machine interfaces. As well as original research papers, the journal publishes short contributions, book reviews and conference reports. All papers are peer-reviewed by at least two referees.
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