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High penetrated renewable energy sources-based AOMPC for microgrid's frequency regulation during weather changes, time-varying parameters and generation unit collapse

机译:基于高穿透的可再生能源的Aompc用于微电网的频率调节,在天气变化,时变参数和生成单位崩溃

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摘要

Using inverter-based topologies and lack of rotational masses can lead to a noticeable reduction in the inertia of modern systems and have detrimental effects on the resiliency, stability and strengths of microgrids. Effective frequency control ancillary services and modern adaptive control mechanisms can be proposed to resolve the mentioned challenges practically. From this perspective, several flexible and intelligent control approaches have been recently introduced to create a balance between generation and load demand during various operational conditions in low-inertia power systems. This study suggests a supportive collaboration between two distributed generations including virtual inertia of wind turbine generator and fast speed micro-turbine based on an adaptive optimal model predictive control (AOMPC). To demonstrate the effectiveness of the proposed framework, the results are compared with the previous controllers like optimal proportional–integral, optimal fractional order proportional–integral–derivative (PID), optimal fuzzy PID, the optimised membership function of fuzzy and adaptive MPC controller during multiple load variations, changes in the weather patterns, unwanted time-varying uncertainties and collapse of power generation units.
机译:使用基于逆变器的拓扑和缺乏旋转质量可以导致现代系统惯性的显着降低,对微电网的弹性,稳定性和强度具有不利影响。有效的频率控制辅助服务和现代自适应控制机制几乎可以解决这些挑战。从这个角度来看,最近曾经推出过几种灵活和智能的控制方法在低惯性电力系统中的各种操作条件下产生和负载需求之间的平衡。本研究表明,基于自适应最优模型预测控制(AOMPC),包括风力涡轮发电机和快速微型涡轮机的两个分布式代代之间的支持性协作。为了证明所提出的框架的有效性,将结果与先前的控制器相比,如最佳比例积分,最佳的分数顺序比例 - 积分 - 衍生(PID),最佳模糊PID,模糊和自适应MPC控制器的优化隶属函数多重负载变化,天气模式的变化,不需要的时变的不确定性和发电单元的崩溃。

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