A hybrid control approach to improve power quality in microgrid systems

IF 13.9 2区 计算机科学 Q1 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE
Nima Khosravi
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引用次数: 0

Abstract

Power quality (PQ) in distributed energy resources (DERs) is paramount for maintaining a stable and efficient electricity supply. The consistency and cleanliness of power are integral to ensuring reliability, sustainability, and optimal performance, thereby supporting a resilient and eco-friendly energy infrastructure. This paper introduces a hybrid control method designed to address two significant challenges in microgrid (MG) applications: active resonance damping (ARD) and unbalanced voltage compensation (UVC). Furthermore, the proposed hybrid method combines effective ARD with UVC at MG terminals. The active damping technique employs an external control level to counteract undesirable resonant harmonics, overcoming control bandwidth limitations. This approach offers simplicity in setup and performance without requiring additional system parameter adjustments. For UVC, the suggested control technique estimates the compensation reference using the dual d-q control, reducing the complexity and cost associated with load current measurement issues. The hybrid method integrates the resonant damping signal and the MG negative sequence reference (NSR) voltage, which are fed into a two-level sine-pulse width modulation block (SPWM) to control the MG converter. Simulation results validate the robustness of the proposed combined method in simultaneously compensating for unbalanced voltage and active resonance.

Graphical abstract

一种改善微电网电能质量的混合控制方法
分布式能源系统中的电能质量对于维持稳定、高效的电力供应至关重要。电力的一致性和清洁度对于确保可靠性、可持续性和最佳性能至关重要,从而支持有弹性和环保的能源基础设施。本文介绍了一种混合控制方法,旨在解决微电网应用中的两个重大挑战:主动共振阻尼(ARD)和不平衡电压补偿(UVC)。此外,所提出的混合方法将有效ARD与MG端UVC相结合。主动阻尼技术采用外部控制电平来抵消不希望的谐振谐波,克服了控制带宽的限制。这种方法提供了简单的设置和性能,而不需要额外的系统参数调整。对于UVC,建议的控制技术使用双d-q控制来估计补偿参考,从而降低了与负载电流测量问题相关的复杂性和成本。该方法将谐振阻尼信号和负序参考电压(NSR)集成到双电平正弦脉宽调制模块(SPWM)中,实现对MG变换器的控制。仿真结果验证了该方法对不平衡电压和主动谐振同步补偿的鲁棒性。图形抽象
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
Artificial Intelligence Review
Artificial Intelligence Review 工程技术-计算机:人工智能
CiteScore
22.00
自引率
3.30%
发文量
194
审稿时长
5.3 months
期刊介绍: Artificial Intelligence Review, a fully open access journal, publishes cutting-edge research in artificial intelligence and cognitive science. It features critical evaluations of applications, techniques, and algorithms, providing a platform for both researchers and application developers. The journal includes refereed survey and tutorial articles, along with reviews and commentary on significant developments in the field.
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